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[Yadav Raj Upadhyay], यादवराज उपाध्याय. "भाषा र पारिभाषिक शब्दावलीको कोशीय प्रारूपः एक विश्लेषण [Lexical Structures of Language and Linguistic Semantics: An Analysis]." Prithvi Journal of Research and Innovation 3, no. 1 (June 2, 2021): 94–111. http://dx.doi.org/10.3126/pjri.v3i1.37438.
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यस शोधन आलेखमा भाषा, भाषा विज्ञानको परिचय तथा शाखाहरूबारे चिनारी प्रस्तुत गर्दै पारिभाषिक शब्दावली र कोशीय प्रारूपबारे खोज विश्लेषण गरिएको छ । भावाभिव्यक्तिको संस्कृति विचार विनिमयको आधार भाषाका बारेमा वैज्ञानिक ढङ्गले अध्ययन गर्ने ज्ञानको शाखा नै भाषा विज्ञान हो । व्याकरण, भाषाशास्त्र हुँदै विकसित भाषा विज्ञानको संरचक पक्षका आधारमा ध्वनि विज्ञान, वणर् विज्ञान, व्याकरण (रूप, रूप सन्धि र वाक्य) र अर्थ विज्ञान प्रमुख शाखाहरू हुन् । अध्ययन विश्लेषणको पद्धतिका आधारमा भाषा विज्ञानका ऐतिहासिक, तुलनात्मक र वणर्नात्मक प्रमुख तिन शाखाहरू छन् । सिद्धान्तकेन्द्री र प्रयोगकेन्द्री आधारमा भाषा विज्ञान सैद्धान्तिक र प्रायोगिक दुई प्रकारका हुन्छन् । भाषा शिक्षण, कोश विज्ञान, शैली विज्ञान, सामाजिक भाषा विज्ञान, मनोभाषा विज्ञान, अनुवाद विज्ञान, कम्प्युटर विज्ञान, व्यतिरेकी भाषा विज्ञान, सङ्कथन विश्लेषण आदि प्रायोगिक भाषा विज्ञानका प्रकारहरू हुन् । भाषाविज्ञानका यी शाखाहरूमा प्रयुक्त परिभाषाका माध्यमबाट बुझ्नु पर्ने सयांै पारिभाषिक तथा प्राविधिक शब्दावलीहरू छन् । यस्ता शब्दावलीहरूलाई शब्दकोशीय ढाँचामा पेस गर्न सकिने कोशीय प्रारूपको सीमित नमुना समेत यहाँ प्रस्तुत गरिएको छ । [Linguistic semantics and lexical structures have been discussed in this paper, introducing language, linguistics and its forms. Linguistics is the scientific study of language and its structure that is associated with the knowledge systems while communicating across cultures. It is a developed form of grammar, including other aspects of language such as sound system, letters, words, sentences and meanings. It has three main branches such as historical linguistics, comparative linguistics and descriptive linguistics. It can also be categorized into two types: theoretical linguistics and applied linguistics. There are other types of linguistics as well that include language teaching, lexicology, stylistics, sociolinguistics, psycholinguistics, translation studies, computational linguistics and narratology are some examples of applied linguistics. Based on these branches of linguistics, there are hundreds of linguistic semantics to be leant in the study of language and its structure. In this paper, they are exemplified as lexical structures of language and linguistic semantics.]
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Karttunen, Lauri. "Word Play." Computational Linguistics 33, no. 4 (December 2007): 443–67. http://dx.doi.org/10.1162/coli.2007.33.4.443.
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This article is a perspective on some important developments in semantics and in computational linguistics over the past forty years. It reviews two lines of research that lie at opposite ends of the field: semantics and morphology. The semantic part deals with issues from the 1970s such as discourse referents, implicative verbs, presuppositions, and questions. The second part presents a brief history of the application of finite-state transducers to linguistic analysis starting with the advent of two-level morphology in the early 1980s and culminating in successful commercial applications in the 1990s. It offers some commentary on the relationship, or the lack thereof, between computational and paper-and-pencil linguistics. The final section returns to the semantic issues and their application to currently popular tasks such as textual inference and question answering.
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Robinson, Justyna A. "A gay paper: why should sociolinguistics bother with semantics?" English Today 28, no. 4 (December 2012): 38–54. http://dx.doi.org/10.1017/s0266078412000399.
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The study of meaning and changes in meaning has enjoyed varying levels of popularity within linguistics. There have been periods during which the exploration of meaning was of prime importance. For instance, in the late 19th century scholars considered the exploration of the etymology of words to be crucial in their quest to find the ‘true’ meaning of lexemes (Geeraerts, 2010; Malkiel, 1993). There have also been periods where semantic analysis was considered redundant to linguistic investigation (Hockett, 1954: 152). In the past 20–30 years semantics has enjoyed a period of revival. This has been mainly led by the advances in cognitive linguistics (and to some extent, historical linguistics) as well by the innovations associated with the development of electronic corpora and computational methods for extracting and tracing changes in the behaviour of the lexicon (cf. Geeraerts, 2010: 168ff, 261ff). However, there are still areas of linguistics which hardly involve lexis in their theoretical and epistemological considerations. One such area is sociolinguistics.
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Stede, Manfred. "Automatic argumentation mining and the role of stance and sentiment." Journal of Argumentation in Context 9, no. 1 (May 4, 2020): 19–41. http://dx.doi.org/10.1075/jaic.00006.ste.
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Abstract Argumentation mining is a subfield of Computational Linguistics that aims (primarily) at automatically finding arguments and their structural components in natural language text. We provide a short introduction to this field, intended for an audience with a limited computational background. After explaining the subtasks involved in this problem of deriving the structure of arguments, we describe two other applications that are popular in computational linguistics: sentiment analysis and stance detection. From the linguistic viewpoint, they concern the semantics of evaluation in language. In the final part of the paper, we briefly examine the roles that these two tasks play in argumentation mining, both in current practice, and in possible future systems.
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DONG, ANDY. "Concept formation as knowledge accumulation: A computational linguistics study." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 20, no. 1 (February 2006): 35–53. http://dx.doi.org/10.1017/s0890060406060033.
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Language plays at least two roles in design. First, language serves as representations of ideas and concepts through linguistic behaviors that represent the structure of thought during the design process. Second, language also performs actions and creates states of affairs. Based on these two perspectives on language use in design, we apply the computational linguistics tools of latent semantic analysis and lexical chain analysis to characterize how design teams engage in concept formation as the accumulation of knowledge represented by lexicalized concepts. The accumulation is described in a data structure comprised by a set of links between elemental lexicalized concepts. The folding together of these two perspectives on language use in design with the information processing theories of the mind afforded by the computational linguistics tools applied creates a new means to evaluate concept formation in design teams. The method suggests that analysis at a linguistic level can characterize concept formation even where process-oriented critiques were limited in their ability to uncover a formal design method that could explain the phenomenon.
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Ali, Mazhar, and Asim Imdad Wagan. "An Analysis of Sindhi Annotated Corpus using Supervised Machine Learning Methods." January 2019 38, no. 1 (January 1, 2019): 185–96. http://dx.doi.org/10.22581/muet1982.1901.15.
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The linguistic corpus of Sindhi language is significant for computational linguistics process, machine learning process, language features identification and analysis, semantic and sentiment analysis, information retrieval and so on. There is little computational linguistics work done on Sindhi text whereas, English, Arabic, Urdu and some other languages are fully resourced computationally. The grammar and morphemes of these languages are analyzed properly using dissimilar machine learning methods. The development and research work regarding computational linguistics are in progress on Sindhi language at this time. This study is planned to develop the Sindhi annotated corpus using universal POS (Part of Speech) tag set and Sindhi POS tag set for the purpose of language features and variation analysis. The features are extracted using TF-IDF (Term Frequency and Inverse Document Frequency) technique. The supervised machine learning model is developed to assess the annotated corpus to know the grammatical annotation of Sindhi language. The model is trained with 80% of annotated corpus and tested with 20% of test set. The cross-validation technique with 10-folds is utilized to evaluate and validate the model. The results of model show the better performance of model as well as confirm the proper annotation to Sindhi corpus. This study described a number of research gaps to work more on topic modeling, language variation, sentiment and semantic analysis of Sindhi language.
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BOSQUE-GIL, J., J. GRACIA, E. MONTIEL-PONSODA, and A. GÓMEZ-PÉREZ. "Models to represent linguistic linked data." Natural Language Engineering 24, no. 6 (October 4, 2018): 811–59. http://dx.doi.org/10.1017/s1351324918000347.
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AbstractAs the interest of the Semantic Web and computational linguistics communities in linguistic linked data (LLD) keeps increasing and the number of contributions that dwell on LLD rapidly grows, scholars (and linguists in particular) interested in the development of LLD resources sometimes find it difficult to determine which mechanism is suitable for their needs and which challenges have already been addressed. This review seeks to present the state of the art on the models, ontologies and their extensions to represent language resources as LLD by focusing on the nature of the linguistic content they aim to encode. Four basic groups of models are distinguished in this work: models to represent the main elements of lexical resources (group 1), vocabularies developed as extensions to models in group 1 and ontologies that provide more granularity on specific levels of linguistic analysis (group 2), catalogues of linguistic data categories (group 3) and other models such as corpora models or service-oriented ones (group 4). Contributions encompassed in these four groups are described, highlighting their reuse by the community and the modelling challenges that are still to be faced.
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Jenset, Gard B. "Mapping meaning with distributional methods." Journal of Historical Linguistics 3, no. 2 (December 31, 2013): 272–306. http://dx.doi.org/10.1075/jhl.3.2.04jen.
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The semantics of existential there is discussed in a diachronic, corpus-based perspective. While previous studies of there have been qualitative or relied on interpreting relative frequencies directly, the present study combines multivariate statistical techniques with linguistic theory through distributional semantics. It is argued that existential uses of there in earlier stages of English were not semantically empty, and that the original meaning was primarily deictic rather than locative. This analysis combines key insights from previous studies of existential there with a Construction Grammar perspective, and discusses some methodological concerns regarding statistical methods for creating computational semantic maps from diachronic corpus data.
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Iomdin, Leonid. "Microsyntactic Annotation of Corpora and its Use in Computational Linguistics Tasks." Journal of Linguistics/Jazykovedný casopis 68, no. 2 (December 1, 2017): 169–78. http://dx.doi.org/10.1515/jazcas-2017-0027.
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Abstract Microsyntax is a linguistic discipline dealing with idiomatic elements whose important properties are strongly related to syntax. In a way, these elements may be viewed as transitional entities between the lexicon and the grammar, which explains why they are often underrepresented in both of these resource types: the lexicographer fails to see such elements as full-fledged lexical units, while the grammarian finds them too specific to justify the creation of individual well-developed rules. As a result, such elements are poorly covered by linguistic models used in advanced modern computational linguistic tasks like high-quality machine translation or deep semantic analysis. A possible way to mend the situation and improve the coverage and adequate treatment of microsyntactic units in linguistic resources is to develop corpora with microsyntactic annotation, closely linked to specially designed lexicons. The paper shows how this task is solved in the deeply annotated corpus of Russian, SynTagRus.
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Jäppinen, H., T. Honkela, H. Hyötyniemi, and A. Lehtola. "A Multilevel Natural Language Processing Model." Nordic Journal of Linguistics 11, no. 1-2 (June 1988): 69–87. http://dx.doi.org/10.1017/s033258650000175x.
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In this paper we describe a multilevel model for natural language processing. The distinct computational strata are motivated by invariant linguistic properties which are progressively uncovered from utterances. We examine each level in detail. The processes are morphological analysis, dependency parsing, logico-semantic analysis and query adaptation. Both linguistic and computational aspects are discussed. In addition to theory, we consider certain engineering viewpoints important and discuss them briefly.
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Fox, Renata. "USING CORPUS LINGUISTICS TO DESCRIBE CORPORATIONS’ IDEOLOGIES." Tourism and hospitality management 12, no. 2 (December 2006): 15–24. http://dx.doi.org/10.20867/thm.12.2.2.
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This article applies corpus linguistics to research the ideologies of Fortune 500 corporations as institutionalised through those corporations’ mission statements. The methodology used is both qualitative and quantitative. Qualitative methodology relates to the semantics of corporations’ ideologies. More precisely, it explains the ideas, beliefs, meanings, and concepts found in corporations’ mission statements, the relation between those ideas, beliefs, meanings, and concepts and society, and what makes those ideas, beliefs, meanings, and concepts meaningful. Quantitative methodology relates to the description and comparison of corporations’ ideologies based on a corpus-driven approach and computational text analysis of a corpus of corporations’ mission statements. Ultimately, through its ideology a corporation creates a symbolic universe: “a matrix of all social and individual meanings” that determines the significance of the corporation and its stakeholders.
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Ploux, Sabine, Stéphanie Dabic, Yves Paulignan, Anne Cheylus, and Tatjana A. Nazir. "Toward a neurolexicology." Mental Lexicon 7, no. 2 (December 7, 2012): 210–36. http://dx.doi.org/10.1075/ml.7.2.04plo.
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This article analyzes the organization of the mental lexicon based on neurophysiological data. The neuroscience literature has devoted many studies to the semantic processing of words. However, the research remains specific to certain categories, studied separately, and does not address the lexicon as a system. In order to provide further insight into the neuronal organization of the lexicon, we conducted an EEG-based semantic decision experiment using words from eight categories (four living and four nonliving categories) as the material. A data-analysis method (correspondence analysis or CA) commonly used in computational linguistics was applied to the electrophysiological signals. The results revealed a two-factor structure: an ontological organization separating the living from the nonliving, and an organization with a human referential structured by proximity to the person. A comparison of the ERP-CA and the linguistic-CA data revealed organizational analogies. Lastly, a tomography software (Loreta®) was used to estimate the cerebral sources associated with the ERP signals.
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Beinborn, Lisa, and Rochelle Choenni. "Semantic Drift in Multilingual Representations." Computational Linguistics 46, no. 3 (November 2020): 571–603. http://dx.doi.org/10.1162/coli_a_00382.
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Multilingual representations have mostly been evaluated based on their performance on specific tasks. In this article, we look beyond engineering goals and analyze the relations between languages in computational representations. We introduce a methodology for comparing languages based on their organization of semantic concepts. We propose to conduct an adapted version of representational similarity analysis of a selected set of concepts in computational multilingual representations. Using this analysis method, we can reconstruct a phylogenetic tree that closely resembles those assumed by linguistic experts. These results indicate that multilingual distributional representations that are only trained on monolingual text and bilingual dictionaries preserve relations between languages without the need for any etymological information. In addition, we propose a measure to identify semantic drift between language families. We perform experiments on word-based and sentence-based multilingual models and provide both quantitative results and qualitative examples. Analyses of semantic drift in multilingual representations can serve two purposes: They can indicate unwanted characteristics of the computational models and they provide a quantitative means to study linguistic phenomena across languages.
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UTSUMI, AKIRA. "A semantic space approach to the computational semantics of noun compounds." Natural Language Engineering 20, no. 2 (January 15, 2013): 185–234. http://dx.doi.org/10.1017/s135132491200037x.
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AbstractThis study examines the ability of a semantic space model to represent the meaning of noun compounds such as ‘information gathering’ or ‘heart disease.’ For a semantic space model to compute the meaning and the attributional similarity (or semantic relatedness) for unfamiliar noun compounds that do not occur in a corpus, the vector for a noun compound must be computed from the vectors of its constituent words using vector composition algorithms. Six composition algorithms (i.e., centroid, multiplication, circular convolution, predication, comparison, and dilation) are compared in terms of the quality of the computation of the attributional similarity for English and Japanese noun compounds. To evaluate the performance of the computation of the similarity, this study uses three tasks (i.e., related word ranking, similarity correlation, and semantic classification), and two types of semantic spaces (i.e., latent semantic analysis-based and positive pointwise mutual information-based spaces). The result of these tasks is that the dilation algorithm is generally most effective in computing the similarity of noun compounds, while the multiplication algorithm is best suited specifically for the positive pointwise mutual information-based space. In addition, the comparison algorithm works better for unfamiliar noun compounds that do not occur in the corpus. These findings indicate that in general a semantic space model, and in particular the dilation, multiplication, and comparison algorithms have sufficient ability to compute the attributional similarity for noun compounds.
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Karlgren, Jussi, and Pentti Kanerva. "High-dimensional distributed semantic spaces for utterances." Natural Language Engineering 25, no. 4 (July 2019): 503–17. http://dx.doi.org/10.1017/s1351324919000226.
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AbstractHigh-dimensional distributed semantic spaces have proven useful and effective for aggregating and processing visual, auditory and lexical information for many tasks related to human-generated data. Human language makes use of a large and varying number of features, lexical and constructional items as well as contextual and discourse-specific data of various types, which all interact to represent various aspects of communicative information. Some of these features are mostly local and useful for the organisation of, for example, argument structure of a predication; others are persistent over the course of a discourse and necessary for achieving a reasonable level of understanding of the content.This paper describes a model for high-dimensional representation for utterance and text-level data including features such as constructions or contextual data, based on a mathematically principled and behaviourally plausible approach to representing linguistic information. The implementation of the representation is a straightforward extension of Random Indexing models previously used for lexical linguistic items. The paper shows how the implementedmodel is able to represent a broad range of linguistic features in a common integral framework of fixed dimensionality, which is computationally habitable, and which is suitable as a bridge between symbolic representations such as dependency analysis and continuous representations used, for example, in classifiers or further machine-learning approaches. This is achieved with operations on vectors that constitute a powerful computational algebra, accompanied with an associative memory for the vectors. The paper provides a technical overview of the framework and a worked through implemented example of how it can be applied to various types of linguistic features.
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Lai, Huei-ling. "Collocation analysis of news discourse and its ideological implications." Pragmatics. Quarterly Publication of the International Pragmatics Association (IPrA) 29, no. 4 (August 21, 2019): 545–70. http://dx.doi.org/10.1075/prag.17028.lai.
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Abstract This study investigates the use of an ethnic term in news discourse from linguistic, discursive, and social-cultural aspects. A more rigorous computational procedure than hitherto used is employed to measure the collocational strength of collocates in news corpora. The results indicate diversified distributions of the collocates regarding their frequency, distance, and semantic connections. The findings enhance the meaning specificity of the term by revealing the characterized reference of this ethnic group, the trends in the choice of news topics, and the ideological representation of this ethnic group in a wider social-cultural context. The findings deepen an understanding of news discourse as the representations of the minority ethnicity in the news media are analyzed through three layers – the linguistic, the discursive, and the social-cultural context. A more precise method of analyzing news texts uncovers ideological effects brought about by media, in turn implying different construal of newsworthiness in news discourse.
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Gluckman, John, and Margit Bowler. "The expression of modality in Logoori." Journal of African Languages and Linguistics 41, no. 2 (October 1, 2020): 195–238. http://dx.doi.org/10.1515/jall-2020-2010.
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Abstract This study presents a theoretically informed description of the expression of modality in Logoori (Luyia; Bantu). We document verbal and non-verbal modal expressions in Logoori, and show how these expressions fit into proposed typologies of modal systems (Kratzer, Angelika. 1981. The notional category of modality. In Hans-Jurgen Eikmeyer & Hannes Rieser (eds.), Words, worlds, and contexts: New approaches in word semantics, 38–74. Berlin: Mouton de Gruyter, Kratzer, Angelika. 1991. Modality. In Armin von Stechow & Dieter Wunderlich (eds.), Semantics: An international handbook of contemporary research, 639–650. Berlin: Mouton de Gruyter; van der Auwera, Johan & Vladimir Plungian. 1998. Modality’s semantic map. Linguistic Typology 2. 79–124. https://doi.org/10.1515/lity.1998.2.1.79; Nauze, Fabrice. 2008. Modality in typological perspective. Amsterdam: Institute for Logic, Language, and Computation PhD thesis). We show that Logoori’s modal system raises some interesting questions regarding the typology and theoretical analysis of modality and its relationship to other kinds of meaning. Our study contributes to the nascent but growing research on modal systems cross linguistically by adding data from an understudied Bantu language.
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Zadeh, L. A. "Foreword." International Journal of Computers Communications & Control 6, no. 3 (September 1, 2011): 385. http://dx.doi.org/10.15837/ijccc.2011.3.2123.
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<p>I feel honored by the dedication of the Special Issue of IJCCC to me. I should like to express my deep appreciation to the distinguished Co-Editors and my good friends, Professors Balas, Dzitac and Teodorescu, and to distinguished contributors, for honoring me. The subjects which are addressed in the Special Issue are on the frontiers of fuzzy logic.<br /> <br /> The Foreword gives me an opportunity to share with the readers of the Journal my recent thoughts regarding a subject which I have been pondering about for many years - fuzzy logic and natural languages. The first step toward linking fuzzy logic and natural languages was my 1973 paper," Outline of a New Approach to the Analysis of Complex Systems and Decision Processes." Two key concepts were introduced in that paper. First, the concept of a linguistic variable - a variable which takes words as values; and second, the concept of a fuzzy if- then rule - a rule in which the antecedent and consequent involve linguistic variables. Today, close to forty years later, these concepts are widely used in most applications of fuzzy logic.<br /> <br /> The second step was my 1978 paper, "PRUF - a Meaning Representation Language for Natural Languages." This paper laid the foundation for a series of papers in the eighties in which a fairly complete theory of fuzzy - logic-based semantics of natural languages was developed. My theory did not attract many followers either within the fuzzy logic community or within the linguistics and philosophy of languages communities. There is a reason. The fuzzy logic community is largely a community of engineers, computer scientists and mathematicians - a community which has always shied away from semantics of natural languages. Symmetrically, the linguistics and philosophy of languages communities have shied away from fuzzy logic.<br /> <br /> In the early nineties, a thought that began to crystallize in my mind was that in most of the applications of fuzzy logic linguistic concepts play an important, if not very visible role. It is this thought that motivated the concept of Computing with Words (CW or CWW), introduced in my 1996 paper "Fuzzy Logic = Computing with Words." In essence, Computing with Words is a system of computation in which the objects of computation are words, phrases and propositions drawn from a natural language. The same can be said about Natural Language Processing (NLP.) In fact, CW and NLP have little in common and have altogether different agendas.<br /> <br /> In large measure, CW is concerned with solution of computational problems which are stated in a natural language. Simple example. Given: Probably John is tall. What is the probability that John is short? What is the probability that John is very short? What is the probability that John is not very tall? A less simple example. Given: Usually Robert leaves office at about 5 pm. Typically it takes Robert about an hour to get home from work. What is the probability that Robert is home at 6:l5 pm.? What should be noted is that CW is the only system of computation which has the capability to deal with problems of this kind. The problem-solving capability of CW rests on two key ideas. First, employment of so-called restriction-based semantics (RS) for translation of a natural language into a mathematical language in which the concept of a restriction plays a pivotal role; and second, employment of a calculus of restrictions - a calculus which is centered on the Extension Principle of fuzzy logic.<br /> <br /> What is thought-provoking is that neither traditional mathematics nor standard probability theory has the capability to deal with computational problems which are stated in a natural language. Not having this capability, it is traditional to dismiss such problems as ill-posed. In this perspective, perhaps the most remarkable contribution of CW is that it opens the door to empowering of mathematics with a fascinating capability - the capability to construct mathematical solutions of computational problems which are stated in a natural language. The basic importance of this capability derives from the fact that much of human knowledge, and especially world knowledge, is described in natural language.<br /> <br /> In conclusion, only recently did I begin to realize that the formalism of CW suggests a new and challenging direction in mathematics - mathematical solution of computational problems which are stated in a natural language. For mathematics, this is an unexplored territory.</p>
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Bayram, A. Burcu, and Vivian Ta. "Measuring common knowledge: latent semantic analysis, linguistic synchrony, and common knowledge in international relations." International Relations 34, no. 2 (September 8, 2019): 180–203. http://dx.doi.org/10.1177/0047117819871996.
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Common knowledge, also called intersubjectivity, is a core theme in the study of international cooperation and diplomacy. Yet International Relations (IR) lacks a method to systematically measure the degree of common knowledge. Drawing from research in computational linguistics, psychology, and communication, we introduce latent semantic analysis (LSA) to measure common knowledge in specific communicative exchanges between actors. We argue that the extent to which speaking partners use words in the same way and get in synch linguistically can be used to measure the degree of common knowledge, and this can be measured by the LSA method. We outline several ways LSA can be valuable to IR scholars and provide an empirical illustration of using this method in the case of Bretton Woods negotiations. The LSA method promises to help IR scholars seize the research opportunities offered by the digital age and build a bridge between qualitative and quantitative methods.
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M. LONGA, VíCTOR. "Making Prehistoric Lines Speak: Inferring Language and Mental Computations from ‘Natural’ Lines of Parietal Art1." Philology 4, no. 2018 (January 1, 2019): 243–78. http://dx.doi.org/10.3726/phil042019.7.
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Abstract According to many archaeologists and paleoanthropologists, the presence of symbolism in the prehistoric archaeological record indicates complex language. Therefore, archaeological remains have usually been analyzed from the perspective of the behavior (in this case, symbolic) they could be associated with. This paper proposes a very different approach, arising from formal linguistics and mathematical theory of computation: to analyze archaeological remains from the perspective of the computational processes and capabilities required for their production. This approach is not concerned with the ‘semantics’ of the pieces (symbolism, etc.), but with the analysis of purely formal features revealing a language-like computational complexity. I will exemplify this approach through the computational analysis of representations of Upper Palaeolithic parietal art, concentrating on the use of ‘natural’ lines, i.e. lines preexisting in the rocks (cracks, fissures, etc.), which were used as anchorage points for many representations. This use of natural lines will be shown to reveal a high computational complexity.
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Tuan, Vu Van. "Communicative Competence of the Fourth Year Students: Basis for Proposed English Language Program." English Language Teaching 10, no. 7 (June 5, 2017): 104. http://dx.doi.org/10.5539/elt.v10n7p104.
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This study on level of communicative competence covering linguistic/grammatical and discourse has aimed at constructing a proposed English language program for 5 key universities in Vietnam. The descriptive method utilized was scientifically employed with comparative techniques and correlational analysis. The researcher treated the surveyed data through frequency counts, means and percentage computations, and analysis of variance/t-test to compare two main area variables. The respondents was 221 students from 5 universities randomly chosen. The major findings of the study generally reveal that the students’ level of communicative competence is a factor of their parents’ academic influence. Their linguistic/grammatical and discourse competence is helped by their chance for formal and intensive learning, conversing with a native speaker of the English language, rich exposure to social media networks, and reading materials written in English. Moreover, the students’ greatest strength along linguistic competence is on the use and function of noun, pronoun and preposition, while their weaknesses are on the use and function of conjunction, adverb, interjection, and verb. It is a general finding that the 4th year students who are linguistically competent on the whole system and structure of a language or of languages in general (consisting of syntax, morphology, inflections, phonology and semantics) have the tendency to speak or write authoritatively about a topic or to engage in conversation. Basing on the findings from this study, an enhancement program was proposed with the certainty that this proposed English language program would bring the best efficiency in the second language acquisition.
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CHOLAKOV, KOSTADIN. "Lexical acquisition and semantic space models: Learning the semantics of unknown words." Natural Language Engineering 20, no. 4 (March 5, 2013): 537–55. http://dx.doi.org/10.1017/s1351324913000053.
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AbstractIn recent studies it has been shown that syntax-based semantic space models outperform models in which the context is represented as a bag-of-words in several semantic analysis tasks. This has been generally attributed to the fact that syntax-based models employ corpora that are syntactically annotated by a parser and a computational grammar. However, if the corpora processed contain words which are unknown to the parser and the grammar, a syntax-based model may lose its advantage since the syntactic properties of such words are unavailable. On the other hand, bag-of-words models do not face this issue since they operate on raw, non-annotated corpora and are thus more robust. In this paper, we compare the performance of syntax-based and bag-of-words models when applied to the task of learning the semantics of unknown words. In our experiments, unknown words are considered the words which are not known to the Alpino parser and grammar of Dutch. In our study, the semantics of an unknown word is defined by finding its most similar word incornetto, a Dutch lexico-semantic hierarchy. We show that for unknown words the syntax-based model performs worse than the bag-of-words approach. Furthermore, we show that if we first learn the syntactic properties of unknown words by an appropriate lexical acquisition method, then in fact the syntax-based model does outperform the bag-of-words approach. The conclusion we draw is that, for words unknown to a given grammar, a bag-of-words model is more robust than a syntax-based model. However, the combination of lexical acquisition and syntax-based semantic models is best suited for learning the semantics of unknown words.
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Ustalov, Dmitry, Alexander Panchenko, Chris Biemann, and Simone Paolo Ponzetto. "Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction." Computational Linguistics 45, no. 3 (September 2019): 423–79. http://dx.doi.org/10.1162/coli_a_00354.
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We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of domains. This algorithm creates an intermediate representation of the input graph, which reflects the “ambiguity” of its nodes. Then, it uses hard clustering to discover clusters in this “disambiguated” intermediate graph. After outlining the approach and analyzing its computational complexity, we demonstrate that Watset shows competitive results in three applications: unsupervised synset induction from a synonymy graph, unsupervised semantic frame induction from dependency triples, and unsupervised semantic class induction from a distributional thesaurus. Our algorithm is generic and can also be applied to other networks of linguistic data.
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Nolan, Brian. "Theoretical and computational considerations of linking constructions in Role and Reference Grammar." Review of Cognitive Linguistics 12, no. 2 (October 31, 2014): 410–42. http://dx.doi.org/10.1075/rcl.12.2.06nol.
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This paper proposes a view of the linguistic construction in Role and Reference Grammar (RRG) in which constructions are posited to be structured grammatical objects with a unique constructional signature that uniquely identifies them. We argue that the construction has an input and an output, and that it contains a local workspace in which the processing of the various lexical and grammatical rules applies, according to the constraints within the constructional object. In recent years there has been a growing recognition that the RRG account of constructions is an under-utilised resource that deserves a wider application to problems in cross-linguistic analysis (Nolan & Diedrichsen, 2013; Nolan & Periñán, 2014). As a functional grammar with strong claims of adequacy, RRG has however had several challenges from Construction Grammar (Butler & Martín Arista, 2009; Goldberg, 2006; Michaelis, 2006, 2010). This paper addresses a number of these challenges. In the view of constructions presented here, the linking over the syntactic, semantic and pragmatic interfaces resides in the body of the construction, and the construction interacts with the lexicon which provides lexical information relevant to the construction. The constructions reside in a construction repository. This model of constructions delivers a means to address the challenges posed to the RRG account of the role and place of constructions within a lexicalist functionalist model of grammar.
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Serigos, Jacqueline. "Using distributional semantics in loanword research: A concept-based approach to quantifying semantic specificity of Anglicisms in Spanish." International Journal of Bilingualism 21, no. 5 (March 15, 2016): 521–40. http://dx.doi.org/10.1177/1367006916635836.
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Aims and objectives: This study aims to redress the paucity of research on the semantics of loanwords, by extending and empirically testing Backus’s ((2001). The role of semantic specificity in insertional codeswitching: Evidence from Dutch-Turkish. Jacobson, Rodolfo (Hg): Codeswitching Worldwide. Bd, 2, 125–154) Specificity Hypothesis – ‘Embedded language elements in code-switching have a high degree of semantic specificity’ (p. 128). Approach: Adopting a concept-based approach to examine loanwords in a large, reliable corpus, the study pursues the following question: Do loanwords have a high degree of semantic specificity relative to their receiving-language equivalents? Specificity is operationalized as an entropy measure of the target word’s environment, the assumption being that more specific words have less variety in their surrounding context. Data and analysis: To test this hypothesis, Anglicisms in a 24-million-word newspaper corpus of Argentine Spanish were processed in three stages: detecting loanwords, selecting semantic equivalents, and measuring specificity. Findings/conclusions: A Wilcoxon Signed-Rank Test revealed that loanwords receive significantly lower entropy scores, that is, they are more specific than their Spanish equivalents. The results suggest a possible motive for adopting loanwords when terms already exist in the source language, namely, to utilize words that provide more nuanced meaning. Originality: Methodologically, this study offers innovative applications of computational methods to loanword research, employing a distributional model to measure entropy. Theoretically, it addresses an underrepresented aspect of loanword adoption, semantics, by extending Backus’s hypothesis to loanwords and increasing its scope to data often viewed as ‘monolingual’. Significance/implications: The conclusions offer novel perspectives on loanwords with existing semantic equivalents, often viewed as ‘unnecessary’ when compared to loanwords that introduce new concepts into the recipient language (e.g. blog). With the notion of specificity, we may understand these loanwords as disruptors to the semantic system of the recipient language, dividing up the semantic space formerly occupied solely by the native equivalent, thus increasing the level of nuance expressed in the original concept.
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Cerutti, Federico, Matthias Thimm, and Mauro Vallati. "An experimental analysis on the similarity of argumentation semantics." Argument & Computation 11, no. 3 (November 10, 2020): 269–304. http://dx.doi.org/10.3233/aac-200907.
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In this paper we ask whether approximation for abstract argumentation is useful in practice, and in particular whether reasoning with grounded semantics – which has polynomial runtime – is already an approximation approach sufficient for several practical purposes. While it is clear from theoretical results that reasoning with grounded semantics is different from, for example, skeptical reasoning with preferred semantics, we investigate how significant this difference is in actual argumentation frameworks. As it turns out, in many graphs models, reasoning with grounded semantics actually approximates reasoning with other semantics almost perfectly. An algorithm for grounded reasoning is thus a conceptually simple approximation algorithm that not only does not need a learning phase – like recent approaches – but also approximates well – in practice – several decision problems associated to other semantics.
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Mason, Zachary J. "CorMet: A Computational, Corpus-Based Conventional Metaphor Extraction System." Computational Linguistics 30, no. 1 (March 2004): 23–44. http://dx.doi.org/10.1162/089120104773633376.
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CorMet is a corpus-based system for discovering metaphorical mappings between concepts. It does this by finding systematic variations in domain-specific selectional preferences, which are inferred from large, dynamically mined Internet corpora. Metaphors transfer structure from a source domain to a target domain, making some concepts in the target domain metaphorically equivalent to concepts in the source domain. The verbs that select for a concept in the source domain tend to select for its metaphorical equivalent in the target domain. This regularity, detectable with a shallow linguistic analysis, is used to find the metaphorical interconcept mappings, which can then be used to infer the existence of higher-level conventional metaphors. Most other computational metaphor systems use small, hand-coded semantic knowledge bases and work on a few examples. Although Cor Met's only knowledge base is Word Net (Fellbaum 1998) it can find the mappings constituting many conventional metaphors and in some cases recognize sentences instantiating those mappings. CorMet is tested on its ability to find a subset of the Master Metaphor List (Lakoff, Espenson, and Schwartz 1991).
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Rienstra, Tjitze, Chiaki Sakama, Leendert van der Torre, and Beishui Liao. "A principle-based robustness analysis of admissibility-based argumentation semantics." Argument & Computation 11, no. 3 (November 10, 2020): 305–39. http://dx.doi.org/10.3233/aac-200520.
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The principle-based approach is a methodology to classify and analyse argumentation semantics. In this paper we classify seven of the main alternatives for argumentation semantics using a set of new robustness principles. These principles complement Baroni and Giacomin’s original classification and deal with the behaviour of a semantics when the argumentation framework changes due to the addition or removal of an attack between two arguments. We distinguish so-called persistence principles and monotonicity principles, where the former deal with the question of whether a labelling or extension of an argumentation framework under a given semantics persists after a change, and the latter with the question of whether new labellings or extensions are created after a change. We furthermore show in which sense labelling-based and extension-based semantics lead to subtly different principles and results. Our results can be used for choosing a semantics for a particular application, or to guide the search for new argumentation semantics, but they have been used also in the design of algorithms.
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MARELLI, MARCO, GEORGIANA DINU, ROBERTO ZAMPARELLI, and MARCO BARONI. "Picking buttercups and eating butter cups: Spelling alternations, semantic relatedness, and their consequences for compound processing." Applied Psycholinguistics 36, no. 6 (July 14, 2014): 1421–39. http://dx.doi.org/10.1017/s0142716414000332.
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ABSTRACTSemantic transparency (ST) is a measure quantifying the strength of meaning association between a compound word (buttercup) and its constituents (butter, cup). Borrowing ideas from computational semantics, we characterize ST in terms of the degree to which a compound and its constituents tend to share the same contexts in everyday usage, and we collect separate measures for different orthographic realizations (solid vs. open) of the same compound. We can thus compare the effects of semantic association in cases in which direct semantic access is likely to take place (buttercup), vis-á-vis forms that encourage combinatorial procedures (butter cup). ST effects are investigated in an analysis of lexical decision latencies. The results indicate that distributionally based ST variables are most predictive of response times when extracted from contexts presenting the compounds as open forms, suggesting that compound processing involves a conceptual combination procedure focusing on the merger of the constituent meanings.
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Lascarides, Alex, and Matthew Stone. "Discourse coherence and gesture interpretation." Gesture 9, no. 2 (September 30, 2009): 147–80. http://dx.doi.org/10.1075/gest.9.2.01las.
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In face-to-face conversation, communicators orchestrate multimodal contributions that meaningfully combine the linguistic resources of spoken language and the visuo-spatial affordances of gesture. In this paper, we characterise this meaningful combination in terms of the COHERENCE of gesture and speech. Descriptive analyses illustrate the diverse ways gesture interpretation can supplement and extend the interpretation of prior gestures and accompanying speech. We draw certain parallels with the inventory of COHERENCE RELATIONS found in discourse between successive sentences. In both domains, we suggest, interlocutors make sense of multiple communicative actions in combination by using these coherence relations to link the actions’ interpretations into an intelligible whole. Descriptive analyses also emphasise the improvisation of gesture; the abstraction and generality of meaning in gesture allows communicators to interpret gestures in open-ended ways in new utterances and contexts. We draw certain parallels with interlocutors’ reasoning about underspecified linguistic meanings in discourse. In both domains, we suggest, coherence relations facilitate meaning-making by RESOLVING the meaning of each communicative act through constrained inference over information made salient in the prior discourse. Our approach to gesture interpretation lays the groundwork for formal and computational models that go beyond previous approaches based on compositional syntax and semantics, in better accounting for the flexibility and the constraints found in the interpretation of speech and gesture in conversation. At the same time, it shows that gesture provides an important source of evidence to sharpen the general theory of coherence in communication.
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Bullock, Barbara E., Jacqueline Serigos, and Almeida Jacqueline Toribio. "Exploring a Loan Translation and Its Consequences in an Oral Bilingual Corpus." Journal of Language Contact 13, no. 3 (July 22, 2021): 612–35. http://dx.doi.org/10.1163/19552629-bja10027.
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Abstract This work applies computational tools that have been used to model loanwords in newspaper corpora to an analysis of a loan translation in an oral bilingual corpus. The explicit goal of the contribution is to argue that a specific collocation found in a corpus of Spanish spoken in Texas, agarrar+NP (e.g., agarrar ayuda), is a loan translation that is calqued on English get+np support verb constructions (e.g., get help). We base our argument on the frequency and the linguistic distribution of the nonconventional usage within and between corpora and on the factors that favor its use. Our findings show that the overall frequency of agarrar is the same in Spanish in Texas as it is in the benchmark monolingual corpus of Mexican Spanish but that it is used differently in the two varieties, a difference that has grammatical, as well as semantic, ramifications.
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Vadakalur Elumalai, Kesavan, Niladri Sekhar Das, Mufleh Salem M. Alqahtani, and Anas Maktabi. "Looking into the Operational Modalities Adopted in Some of the POS Tagging Tools in Identification of Contextual Part-of-Speech of Words in Texts." International Journal of Applied Linguistics and English Literature 8, no. 6 (November 30, 2019): 92. http://dx.doi.org/10.7575/aiac.ijalel.v.8n.6p.92.
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Part-of-speech (POS) tagging is an indispensable method of text processing. The main aim is to assign part-of-speech to words after considering their actual contextual syntactic-cum-semantic roles in a piece of text where they occur (Siemund & Claridge 1997). This is a useful strategy in language processing, language technology, machine learning, machine translation, and computational linguistics as it generates a kind of output that enables a system to work with natural language texts with greater accuracy and success. Part-of-speech tagging is also known as ‘grammatical annotation’ and ‘word category disambiguation’ in some area of linguistics where analysis of form and function of words are important avenues for better comprehension and application of texts. Since the primary task of POS tagging involves a process of assigning a tag to each word, manually or automatically, in a piece of natural language text, it has to pay adequate attention to the contexts where words are used. This is a tough challenge for a system as it normally fails to know how word carries specific linguistic information in a text and what kind of larger syntactic frames it requires for its operation. The present paper takes up this issue into consideration and tries to critically explore how some of the well-known POS tagging systems are capable of handling this kind of challenge and if these POS tagging systems are at all successful in assigning appropriate POS tags to words without accessing information from extratextual domains. The novelty of the paper lies in its attempt for looking into some of the POS tagging schemes proposed so far to see if the systems are actually successful in dealing with the complexities involved in tagging words in texts. It also checks if the performance of these systems is better than manual POS tagging and verifies if information and insights gathered from such enterprises are at all useful for enhancing our understanding about identity and function of words used in texts. All these are addressed in this paper with reference to some of the POS taggers available to us. Moreover, the paper tries to see how a POS tagged text is useful in various applications thereby creating a sense of awareness about multifunctionality of tagged texts among language users.
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Blanke, Tobias, Michael Bryant, and Mark Hedges. "Understanding memories of the Holocaust—A new approach to neural networks in the digital humanities." Digital Scholarship in the Humanities 35, no. 1 (January 8, 2019): 17–33. http://dx.doi.org/10.1093/llc/fqy082.
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Abstract This article addresses an important challenge in artificial intelligence research in the humanities, which has impeded progress with supervised methods. It introduces a novel method to creating test collections from smaller subsets. This method is based on what we will introduce as distant supervision’ and will allow us to improve computational modelling in the digital humanities by including new methods of supervised learning. Using recurrent neural networks, we generated a training corpus and were able to train a highly accurate model that qualitatively and quantitatively improved a baseline model. To demonstrate our new approach experimentally, we employ a real-life research question based on existing humanities collections. We use neural network based sentiment analysis to decode Holocaust memories and present a methodology to combine supervised and unsupervised sentiment analysis to analyse the oral history interviews of the United States Holocaust Memorial Museum. Finally, we employed three advanced methods of computational semantics. These helped us decipher the decisions by the neural network and understand, for instance, the complex sentiments around family memories in the testimonies.
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Lu, Guangquan, and Jihong Huang. "Learning Representation From Concurrence-Words Graph For Aspect Sentiment Classification." Computer Journal 64, no. 7 (July 2021): 1069–79. http://dx.doi.org/10.1093/comjnl/bxab104.
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Abstract Aspect sentiment classification is an important research topic in natural language processing and computational linguistics, assisting in automatically review analysis and emotional tendency judgement. Different from extant methods that focus on text sequence representations, this paper presents a network framework to learn representation from concurrence-words relation graph (LRCWG), so as to improve the Macro-F1 and accuracy. The LRCWG first employs the multi-head attention mechanism to capture the sentiment representation from the sentences which can learn the importance of text sequence representation. And then, it leverages the priori sentiment dictionary information to construct the concurrence relations of sentiment words with Graph Convolution Network (GCN). This assists in that the learnt context representation can keep both the semantics integrity and the features of sentiment concurrence-words relations. The designed algorithm is experimentally evaluated with all the five benchmark datasets and demonstrated that the proposed aspect sentiment classification can significantly improve the prediction performance of learning task.
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Wei, Bin, and Henry Prakken. "An analysis of critical-link semantics with variable degrees of justification." Argument & Computation 7, no. 1 (July 5, 2016): 35–53. http://dx.doi.org/10.3233/aac-160003.
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Oswald, Steve, Sara Greco, Johanna Miecznikowski, Chiara Pollaroli, and Andrea Rocci. "Argumentation and meaning." Journal of Argumentation in Context 9, no. 1 (May 4, 2020): 1–18. http://dx.doi.org/10.1075/jaic.00005.osw.
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Abstract This special issue aims to explore the semantic and pragmatic dimensions of meaning in terms of their significance and relevance in the study of argumentation. Accordingly, the contributors to the project, who have all presented their work during the 2nd Argumentation and Language conference, which took place in Lugano in February 2018,1 have been specifically instructed to produce papers which explicitly tackle the importance of the study of meaning for that of argumentative practices. All papers therefore cover at least one aspect of this complex relationship between argumentation and meaning, which contributes to delivering a state-of-the-art panorama on the issue. Drawing from computational linguistics, semantics, pragmatics and discourse analysis, the contributions to this special issue will illuminate how the study of meaning in its different forms may provide valuable insights for the study of people’s argumentative practices in different contexts, ranging from the political to the private sphere. This introductory discussion tackles specific aspects of the intricate relationship between pragmatic inference and argumentative inference – that is, between meaning and argumentation –, provides a brief survey of existing interfaces between the study of meaning and that of argumentation, and concludes with a presentation of the contributions to this special issue.
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Thessen, Anne, Jenette Preciado, Payoj Jain, James Martin, Martha Palmer, and Riyaz Bhat. "Automated Trait Extraction using ClearEarth, a Natural Language Processing System for Text Mining in Natural Sciences." Biodiversity Information Science and Standards 2 (May 22, 2018): e26080. http://dx.doi.org/10.3897/biss.2.26080.
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The cTAKES package (using the ClearTK Natural Language Processing toolkit Bethard et al. 2014,http://cleartk.github.io/cleartk/) has been successfully used to automatically read clinical notes in the medical field (Albright et al. 2013, Styler et al. 2014). It is used on a daily basis to automatically process clinical notes and extract relevant information by dozens of medical institutions. ClearEarth is a collaborative project that brings together computational linguistics and domain scientists to port Natural Language Processing (NLP) modules trained on the same types of linguistic annotation to the fields of geology, cryology, and ecology. The goal for ClearEarth in the ecology domain is the extraction of ecologically-relevant terms, including eco-phenotypic traits from text and the assignment of those traits to taxa. Four annotators used Anafora (an annotation software; https://github.com/weitechen/anafora) to mark seven entity types (biotic, aggregate, abiotic, locality, quality, unit, value) and six reciprocal property types (synonym of/has synonym, part of/has part, subtype/supertype) in 133 documents from primarily Encyclopedia of Life (EOL) and Wikipedia according to project guidelines (https://github.com/ClearEarthProject/AnnotationGuidelines). Inter-annotator agreement ranged from 43% to 90%. Performance of ClearEarth on identifying named entities in biology text overall was good (precision: 85.56%; recall: 71.57%). The named entities with the best performance were organisms and their parts/products (biotic entities - precision: 72.09%; recall: 54.17%) and systems and environments (aggregate entities - precision: 79.23%; recall: 75.34%). Terms and their relationships extracted by ClearEarth can be embedded in the new ecocore ontology after vetting (http://www.obofoundry.org/ontology/ecocore.html). This project enables use of advanced industry and research software within natural sciences for downstream operations such as data discovery, assessment, and analysis. In addition, ClearEarth uses the NLP results to generate domain-specific ontologies and other semantic resources.
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WANG, YINGXU. "ON FORMAL AND COGNITIVE SEMANTICS FOR SEMANTIC COMPUTING." International Journal of Semantic Computing 04, no. 02 (June 2010): 203–37. http://dx.doi.org/10.1142/s1793351x10000833.
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Semantics is the meaning of symbols, notations, concepts, functions, and behaviors, as well as their relations that can be deduced onto a set of predefined entities and/or known concepts. Semantic computing is an emerging computational methodology that models and implements computational structures and behaviors at semantic or knowledge level beyond that of symbolic data. In semantic computing, formal semantics can be classified into the categories of to be, to have, and to do semantics. This paper presents a comprehensive survey of formal and cognitive semantics for semantic computing in the fields of computational linguistics, software science, computational intelligence, cognitive computing, and denotational mathematics. A set of novel formal semantics, such as deductive semantics, concept-algebra-based semantics, and visual semantics, is introduced that forms a theoretical and cognitive foundation for semantic computing. Applications of formal semantics in semantic computing are presented in case studies on semantic cognition of natural languages, semantic analyses of computing behaviors, behavioral semantics of human cognitive processes, and visual semantic algebra for image and visual object manipulations.
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Pienemann, Manfred. "COALA-A computational system for interlanguage analysis." Interlanguage studies bulletin (Utrecht) 8, no. 1 (February 1992): 59–92. http://dx.doi.org/10.1177/026765839200800104.
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This article describes a computational system for the linguistic analysis of language acquisition data (COALA). The system is a combined AI and database tool which allows the user to form highly complex queries about morphosyntactic and semantic structures contained in large sets of data. COALA identifies those sentences that meet the linguistic criteria defined by the user. It allows the user to freely define such linguistic contexts and to step through the sentences identified by the system. COALA then rapidly displays those sentences in their original discourse context. Additionally, COALA can perform statistical analyses in response to structural linguistic queries.This article contains (1) a discussion of the computational approach taken in the design of COALA, (2) a description of the functionality of the system, and (3) a reflection on the validity of the analytical categories contained therein.
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Di Sciullo, Anna Maria. "Deriving coordinate nouns with Merge and Principles of efficient computation." Revista Linguíʃtica 16, Esp. (November 7, 2020): 85–108. http://dx.doi.org/10.31513/linguistica.2020.v16nesp.a39406.
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We analyze coordinate nouns in English and derive their properties from Merge and Principles of efficient computation. The proposed analysis relies on extended projections for the coordinate conjunction and provides derivations to the interfaces with consequences for the externalization of the coordinator and the semantic interpretation of the coordinate nouns. The proposed analysis challenges associative theories of learning. It also challenges the view that apparently simplex forms, two-words expressions, are remnants of a previous stage in the evolution of language.-----------------------------------------------------------------------------DERIVANDO NOMES COORDENADOS COM MERGE E PRINCÍPIOS DE COMPUTAÇÃO EFICIENTEAnalisamos nomes coordenados em inglês e derivamos suas propriedades a partir de Merge e de Princípios de computação eficiente. A análise proposta baseia-se em projeções estendidas para as conjunções coordenadas e fornece derivações para as interfaces com consequências para a externalização do coordenador e a interpretação semântica dos nomes coordenados. A análise proposta desafia as teorias associativas de aprendizagem. Também desafia a visão de que formas aparentemente simples, expressões de duas palavras, são resquícios de um estágio anterior na evolução da linguagem.---Original em inglês.
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Bablu Singh, Y., Th Mamata Devi, and Ch Yashawanta Singh. "Manipuri Morphological Analysis." Asian Journal of Computer Science and Technology 9, no. 2 (November 5, 2020): 4–10. http://dx.doi.org/10.51983/ajcst-2020.9.2.2174.
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Morphological analysis is the basic foundation in Natural Language Processing applications including Syntax Parsing, Machine Translation (MT), Information Retrieval (IR) and Automatic Indexing. Morphological Analysis can provide valuable information for computer based linguistics task such as Lemmatization and studies of internal structure of the words or the feature values of the word. Computational Morphology is the application of morphological rules in the field of Computational Linguistics, and it is the emerging area in AI, which studies the structure of words, which are formed by combining smaller units of linguistics information, called morphemes: the building blocks of words. It provides about Semantic and Syntactic role in a sentence. It can analyze the Manipuri word forms and produces grammatical information, which is associated with the lexicon. Morphological Analyzer for Manipuri language has been tested on 4500 Manipuri lexicons in Shakti Standard Format (SSF) using Meitei Mayek Unicode as source; thereby an accuracy of 84% has been obtained on a manual check.
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Ito, Noriko, Toru Sugimoto, Yusuke Takahashi, Shino Iwashita, and Michio Sugeno. "Computational Models of Language Within Context and Context-Sensitive Language Understanding." Journal of Advanced Computational Intelligence and Intelligent Informatics 10, no. 6 (November 20, 2006): 782–90. http://dx.doi.org/10.20965/jaciii.2006.p0782.
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We propose two computational models - one of a language within context based on systemic functional linguistic theory and one of context-sensitive language understanding. The model of a language within context called the Semiotic Base characterizes contextual, semantic, lexicogrammatical, and graphological aspects of input texts. The understanding process is divided into shallow and deep analyses. Shallow analysis consists of morphological and dependency analyses and word concept and case relation assignment, mainly by existing natural language processing tools and machine-readable dictionaries. Results are used to detect the contextual configuration of input text in contextual analysis. This is followed by deep analyses of lexicogrammar, semantics, and concepts, conducted by referencing a subset of resources related to the detected context. Our proposed models have been implemented in Java and verified by integrating them into such applications as dialog-based question-and-answer (Q&A).
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Rigo, Sandro José, Isa Mara da Rosa Alves, and Jorge Luis Victória Barbosa. "A Linguistic Approach to Identify the Affective Dimension Expressed in Textual Messages." International Journal of Information and Communication Technology Education 11, no. 1 (January 2015): 44–59. http://dx.doi.org/10.4018/ijicte.2015010103.
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The digital mediation resources used in Distance Education can hinder the teacher's perception about the student's state of mind. However, the textual expression in natural language is widely encouraged in most Distance Education courses, through the use of Virtual Learning Environments and other digital tools. This fact has motivated research efforts in order to identify feelings expressed by students in textual messages. A significant part of the known approaches in this area apply textual analysis without a deep linguistic representation, which can lead to some weakness in the results obtained. This paper reports an approach using theories of Computational Lexical Semantics for the representation of the lexicon of emotion. The methodology was developed through studies regarding corpus analysis, lexical unit description, and the implementation of a computational system to identify the feelings expressed in the textual messages in natural language, using the lexicon of emotion. This system was used in evaluation experiments that indicate improvements when comparing the adopted approach with other similar approaches.
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Енкарнацьйон Санчеc Аренас and Ессам Басем. "Cognitive Exploration of ‘Traveling’ in the Poetry of Widad Benmoussa." East European Journal of Psycholinguistics 5, no. 2 (December 28, 2018): 6–15. http://dx.doi.org/10.29038/eejpl.2018.5.2.are.
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The concept of motion is central to the human cognition and it is universally studied in cognitive linguistics. This research paper investigates concept of motion, with special reference to traveling, in the poetry of Widad Benmoussa. It mainly focuses on the cognitive dimensions underlying the metaphorical representation of traveling. To this end, the research conducts a semi-automated analysis of a corpus representing Widad’s poetic collections. MetaNet’s physical path is mainly used to reveal the cognitive respects of traveling. The personae the poetess assigns are found to pursue a dynamic goal through activation of several physical paths. During the unstable romantic relations, several travel impediments are met. Travel stops and detours, travel companions, paths in journey as well as changing travel destinations are the most stressed elements of ‘Traveling’ respects. With such a described high frequency of sudden departures and hopping, the male persona the poetess assigns evinces typical features of 'wanderlust' or dromomania.
References
Arenas, E. S. (2018). Exploring pornography in Widad Benmoussa’s poetry using LIWC and corpus tools. Sexuality & Culture, 22(4), 1094–1111.
Baicchi, A. (2017). The relevance of conceptual metaphor in semantic interpretation. Estetica. Studi e Ricerche, 7(1), 155–170.
Carey, A. L., Brucks, M. S., Küfner, A. C., Holtzman, N. S., Back, M. D., Donnellan, M. B., ... & Mehl, M. R. (2015). Narcissism and the use of personal pronouns revisited. Journal of Personality and Social Psychology, 109(3), e1.
David, O., & Matlock, T. (2018). Cross-linguistic automated detection of metaphors for poverty and cancer. Language and Cognition, 10(3), 467–493.
David, O., Lakoff, G., & Stickles, E. (2016). Cascades in metaphor and grammar. Constructions and Frames, 8(2), 214–255.
Essam, B. A. (2016). Nizarre Qabbani’s original versus translated pornographic ideology: A corpus-based study. Sexuality & Culture, 20(4), 965–986
Forceville, C. (2016). Conceptual metaphor theory, blending theory, and other cognitivist perspectives on comics. The Visual Narrative Reader, 89–114.
Gibbs Jr, R. W. (2011). Evaluating conceptual metaphor theory. Discourse Processes, 48(8), 529–562.
Kövecses, Z. (2008). Conceptual metaphor theory: Some criticisms and alternative proposals. Annual Review of Cognitive Linguistics, 6(1), 168–184.
Lakoff, G. (2014). Mapping the brain's metaphor circuitry: Metaphorical thought in everyday reason. Frontiers in Human Neuroscience, 8, 958.
Lakoff, G., & Johnson, M. (2008). Metaphors We Live By. University of Chicago press.
Lee, M. G., & Barnden, J. A. (2001). Mental metaphors from the Master Metaphor List: Empirical examples and the application of the ATT-Meta system. Cognitive Science Research Papers-University of Birmingham CSRP.
Lönneker-Rodman, B. (2008). The Hamburg metaphor database project: issues in resource creation. Language Resources and Evaluation, 42(3), 293–318.
Martin, J. H. (1994). Metabank: A knowledge‐base of metaphoric language conventioms. Computational Intelligence, 10(2), 134–149.
MetaNet Web Site: https://metanet.icsi.berkeley.edu/metanet/
Pennebaker, J. W., Boyd, R. L., Jordan, K., & Blackburn, K. (2015). The development and psychometric properties of LIWC2015. Retrieved from https://repositories.lib.utexas.edu/ handle/2152/31333
Santarpia, A., Blanchet, A., Venturini, R., Cavallo, M., & Raynaud, S. (2006, August). La catégorisation des métaphores conceptuelles du corps. In Annales Médico-psychologiques, revue psychiatrique. Vol. 164, No. 6. (pp. 476-485). Elsevier Masson.
Stickles, E., David, O., Dodge, E. K., & Hong, J. (2016). Formalizing contemporary conceptual metaphor theory. Constructions and Frames, 8(2), 166–213
Tausczik, Y. R., & Pennebaker, J. W. (2010). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology,29(1), 24–54.
Sources
Benmoussa, W. (2001). I have Roots in Air (in Arabic). Morocco: Ministry of Culture.
Benmoussa, W. (2006). Between Two Clouds (in Arabic and French). Morocco: Marsam Publishing House.
Benmoussa, W. (2007). I Opened It on You (in Arabic). Morocco: Marsam Publishing House.
Benmoussa, W. (2008). Storm in a Body (in Arabic). Morocco: Marsam Publishing House.
Benmoussa, W. (2010). I Hardly Lost my Narcissism (in Arabic). Syria: Ward Publishing House.
Benmoussa, W. (2014). I Stroll Along This Life. Morocco: Tobkal Publishing House
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Тарабань, Роман, Кодуру Лакшмоджі, Марк ЛаКур, and Філіп Маршалл. "Finding a Common Ground in Human and Machine-Based Text Processing." East European Journal of Psycholinguistics 5, no. 1 (June 30, 2018): 83–91. http://dx.doi.org/10.29038/eejpl.2018.5.1.tar.
Full textAbstract:
Language makes human communication possible. Apart from everyday applications, language can provide insights into individuals’ thinking and reasoning. Machine-based analyses of text are becoming widespread in business applications, but their utility in learning contexts are a neglected area of research. Therefore, the goal of the present work is to explore machine-assisted approaches to aid in the analysis of students’ written compositions. A method for extracting common topics from written text is applied to 78 student papers on technology and ethics. The primary tool for analysis is the Latent Dirichlet Allocation algorithm. The results suggest that this machine-based topic extraction method is effective and supports a promising prospect for enhancing classroom learning and instruction. The method may also prove beneficial in other applied applications, like those in clinical and counseling practice.
References
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet Allocation. Journal of Machine Learning Research 3, 993-1022.
Bruner, J. (1990). Acts of meaning. Cambridge, MA: Harvard University Press.
Chen, K. Y. M., & Wang, Y. (2007). Latent dirichlet allocation. http://acsweb.ucsd.edu/~yuw176/ report/lda.pdf.
Chung, C. K., & Pennebaker, J. W. (2008). Revealing dimensions of thinking in open-ended self-descriptions: An automated meaning extraction method for natural language. Journal of research in personality, 42(1), 96-132.
Feldman, S. (1999). NLP meets the Jabberwocky: Natural language processing in information retrieval. Online Magazine, 23, 62-73. Retrieved from: http://www.onlinemag.net/OL1999/ feldmann5.html
Mishlove, J. (2010). https://www.youtube.com/watch?v=0XTDLq34M18 (Accessed June 12, 2018).
Ostrowski, D. A. (2015). Using latent dirichlet allocation for topic modelling in twitter. In Semantic Computing (ICSC), 2015 IEEE International Conference (pp. 493-497). IEEE.
Pennebaker, J. W. (2004). Theories, therapies, and taxpayers: On the complexities of the expressive writing paradigm. Clinical Psychology: Science and Practice, 11(2), 138-142.
Pennebaker, J.W., Boyd, R.L., Jordan, K., & Blackburn, K. (2015). The development and psychometric properties of LIWC 2015. Austin, TX: University of Texas at Austin.
Pennebaker, J. W., Chung, C. K., Frazee, J., Lavergne, G. M., & Beaver, D. I. (2014). When small words foretell academic success: The case of college admissions essays. PLoS ONE, 9(12), e115844.
Pennebaker, J. W., & King, L. A. (1999). Linguistic styles: Language use as an individual difference. Journal of Personality and Social Psychology, 77(6), 1296-1312.
Recchia, G., Sahlgren, M., Kanerva, P., & Jones, M. N. (2015). Encoding sequential information in semantic space models: Comparing holographic reduced representation and random permutation. Computational intelligence and neuroscience, 2015, 1-18.
Salzmann, Z. (2004). Language, Culture, and Society: An Introduction to Linguistic Anthropology (3rd ed). Westview Press.
Schank, R. C., Goldman, N. M., Rieger III, C. J., & Riesbeck, C. (1973). MARGIE: Memory analysis response generation, and inference on English. In IJCAI, 3, 255-261.
Taraban, R., Marcy, W. M., LaCour Jr., M. S., & Burgess II, R. A. (2017). Developing machine-assisted analysis of engineering students’ ethics course assignments. Proceedings of the American Society of Engineering Education (ASEE) Annual Conference, Columbus, OH. https://www.asee.org/public/conferences/78/papers/19234/view.
Taraban, R., Marcy, W. M., LaCour, M. S., Pashley, D., & Keim, K. (2018). Do engineering students learn ethics from an ethics course? Proceedings of the American Society of Engineering Education – Gulf Southwest (ASEE-GSW) Annual Conference, Austin, TX. http://www.aseegsw18.com/papers.html.
Taraban, R., & Marshall, P. H. (2017). Deep learning and competition in psycholinguistic research. East European Journal of Psycholinguistics, 4(2), 67-74.
Weizenbaum, J. (1966). ELIZA—a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1), 36-45.
Winograd, T. (1972). Understanding natural language. New York: Academic Press.
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Boleda, Gemma. "Distributional Semantics and Linguistic Theory." Annual Review of Linguistics 6, no. 1 (January 14, 2020): 213–34. http://dx.doi.org/10.1146/annurev-linguistics-011619-030303.
Full textAbstract:
Distributional semantics provides multidimensional, graded, empirically induced word representations that successfully capture many aspects of meaning in natural languages, as shown by a large body of research in computational linguistics; yet, its impact in theoretical linguistics has so far been limited. This review provides a critical discussion of the literature on distributional semantics, with an emphasis on methods and results that are relevant for theoretical linguistics, in three areas: semantic change, polysemy and composition, and the grammar–semantics interface (specifically, the interface of semantics with syntax and with derivational morphology). The goal of this review is to foster greater cross-fertilization of theoretical and computational approaches to language as a means to advance our collective knowledge of how it works.
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GARCIA, MARCOS, and PABLO GAMALLO. "Exploring the effectiveness of linguistic knowledge for biographical relation extraction." Natural Language Engineering 21, no. 4 (October 18, 2013): 519–51. http://dx.doi.org/10.1017/s1351324913000314.
Full textAbstract:
AbstractMachine learning techniques have been implemented to extract instances of semantic relations using diverse features based on linguistic knowledge, such as tokens, lemmas, PoS-tags, or dependency paths. However, there has been little work aiming to know which of these features works better in the relation extraction task, and less in languages other than English. In this paper, various features representing different levels of linguistic knowledge are systematically evaluated for biographical relation extraction. The effectiveness of these features was measured by training several supervised classifiers that only differ in the type of linguistic knowledge used to define their features. The experiments performed in this paper show that some basic linguistic knowledge (provided by lemmas and their combination in bigrams) behaves better than other complex features, such as those based on syntactic analysis. Furthermore, some feature combinations using different levels of analysis are proposed in order (i) to avoid feature overlapping as well as (ii) to evaluate the use of computationally inexpensive and widespread tools such as tokenization and lemmatization. This paper also describes two new freely available corpora for biographical relation extraction in Portuguese and Spanish, built by means of a distant-supervision strategy. Experiments were performed with five semantic relations and two languages, using these corpora.
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Evans, Hywel. "Simpler semantics for computational and cognitive linguistics." Investigationes Linguisticae 41 (December 11, 2019): 17–31. http://dx.doi.org/10.14746/il.2018.41.2.
Full textAbstract:
Certain consequences are considered regarding a simpler, more cognitively plausible treatment of semantics in SignBased Construction Grammar, a cognitive, unification- based theory of language. It is proposed that a construction grammar may be able to improve its coverage of core linguistic phenomena in line with minimalist goals (Chomsky 1993). Suggestions are offered regarding relative clauses and wh-expressions to show that a more straightforward account is available, one that allows a unified treatment of scope for quantifiers and wh-expressions.
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Fan, Min, and Shanwen Xu. "Research on Discourse Coherence based on the Analysis Model of Event Chain from the Perspective of Computational Linguistics." E3S Web of Conferences 189 (2020): 03025. http://dx.doi.org/10.1051/e3sconf/202018903025.
Full textAbstract:
With the rapid development of network technology, natural language processing has also entered a boom period. Probability and data-driven methods have been widely used in natural language processing. The need for people to extract and retrieve information from the Internet is also increasing, and more and more researchers are trying to use computers to process content related to discourse coherence. Based on the event chain of the text semantic structure representation, this paper proposes a text semantic structure representation model, on the basis of which, text coherent resources can be used for the task of text semantic analysis. Event chain is a necessary condition for discourse coherence, which can be transformed into a computable event chain analysis problem, and can be further formalized as discourse-oriented partial dependency analysis of sentences.
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Voppel, Alban, Janna de Boer, Fleur Slegers, Hugo Schnack, and Iris Sommer. "S136. CLASSIFYING SCHIZOPHRENIA USING PHONOLOGICAL, SEMANTIC AND SYNTACTIC FEATURES OF LANGUAGE; A COMBINATORY MACHINE LEARNING APPROACH." Schizophrenia Bulletin 46, Supplement_1 (April 2020): S87. http://dx.doi.org/10.1093/schbul/sbaa031.202.
Full textAbstract:
Abstract Background The diagnosis of schizophrenia is currently based on anamnesis and psychiatric examination only. Language biomarkers may be useful to provide a quantitative and reproducible risk estimate for this spectrum of disorders. While people with schizophrenia spectrum disorders may show one or more language abnormalities, such as incoherence, affective flattening, failure of reference as well as changes in sentence length and complexity, the clinical picture can vary largely between individuals and language abnormalities will reflect this heterogeneity. Computational linguistics can be used to quantify these features of language. Because of the heterogeneous character of the various symptoms present in schizophrenia spectrum subjects, we expect some subjects to show semantic incoherence, while others may have more affective symptoms such as monotonous speech. Here, we combine phonological, semantic and syntactic features of semi-spontaneous language with machine learning algorithms for classification in order to develop a biomarker sensitive to the broad spectrum of schizophrenia. Methods Semi-spontaneous natural language samples were collected from 50 subjects with schizophrenia spectrum disorders and 50 age, gender and parental education matched controls, using recorded neutral-topic, open-ended interviews. The audio samples were speaker coded; audio belonging to the subject was extracted and transcribed. Phonological features were extracted using OpenSMILE; semantic features were calculated using a word2vec model using a moving windows of coherence approach, and finally syntactic aspects were calculated using the T-scan tool. Feature reduction was applied to each of the domains. To distinguish groups, results from machine learning classifiers trained using leave-one-out cross-validation on each of these aspects were combined, incorporating a voting mechanism. Results The machine-learning classifier approach obtained 75–78% accuracy for the semantic, syntactic and phonological domains individually. As most distinguishing features of their respective domain, we found reduced timbre and intonation for the phonological domain, increased variance of coherence for the semantic domain and decreased complexity of speech in the syntactic domain. The combined approach, using a voting algorithm across the domains, achieved an accuracy of 83% and a precision score of 89%. No significant differences in age, gender or parental education between healthy controls and subjects with schizophrenia spectrum disorders was found. Discussion In this study we demonstrated that computational features derived from different linguistic domains capture aspects of symptomatic language of schizophrenia spectrum disorder subjects. The combination of these features was useful to improve classification for this heterogeneous disorder, as we showed high accuracy and precision from the language parameters in distinguishing schizophrenia patients from healthy controls. These values are better than those obtained with imaging or blood analyses, while language is a more easily obtained and cheaper measure than those derived from other methods. Validation in an independent sample is required, and further features of differentiation should be extracted for their respective domains. Our positive results in using language abnormalities to automatically detect schizophrenia show that computational linguistics is a promising method in the search for reliable markers in psychiatry.