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Journal articles on the topic 'Syntactical similarity'
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Wagner, Stefan, Asim Abdulkhaleq, Ivan Bogicevic, Jan-Peter Ostberg, and Jasmin Ramadani. "How are functionally similar code clones syntactically different? An empirical study and a benchmark." PeerJ Computer Science 2 (March 2, 2016): e49. http://dx.doi.org/10.7717/peerj-cs.49.
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Background. Today, redundancy in source code, so-called “clones” caused by copy&paste can be found reliably using clone detection tools. Redundancy can arise also independently, however, not caused by copy&paste. At present, it is not clear how onlyfunctionally similar clones(FSC) differ from clones created by copy&paste. Our aim is to understand and categorise the syntactical differences in FSCs that distinguish them from copy&paste clones in a way that helps clone detection research.Methods. We conducted an experiment using known functionally similar programs in Java and C from coding contests. We analysed syntactic similarity with traditional detection tools and explored whether concolic clone detection can go beyond syntax. We ran all tools on 2,800 programs and manually categorised the differences in a random sample of 70 program pairs.Results. We found no FSCs where complete files were syntactically similar. We could detect a syntactic similarity in a part of the files in <16% of the program pairs. Concolic detection found 1 of the FSCs. The differences between program pairs were in the categories algorithm, data structure, OO design, I/O and libraries. We selected 58 pairs for an openly accessible benchmark representing these categories.Discussion. The majority of differences between functionally similar clones are beyond the capabilities of current clone detection approaches. Yet, our benchmark can help to drive further clone detection research.
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Taybe Elhadi, Mohamed. "Using Text's Terms and Syntactical Properties for Document Similarity." International Journal of Intelligent Information Systems 5, no. 6 (2016): 82. http://dx.doi.org/10.11648/j.ijiis.20160506.11.
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Lee, Ju Hyun, Michael J. Ostwald, and Ning Gu. "A Justified Plan Graph (JPG) grammar approach to identifying spatial design patterns in an architectural style." Environment and Planning B: Urban Analytics and City Science 45, no. 1 (2016): 67–89. http://dx.doi.org/10.1177/0265813516665618.
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This paper presents a hybrid approach that selectively merges aspects of both the theories of Shape Grammar and Space Syntax to investigate spatial design patterns. The paper describes the development of a generic Justified Plan Graph (g-JPG) grammar. This grammatically nuanced, syntactically derived approach is then demonstrated through a more specific JPG (s-JPG) grammar to identify spatial design patterns in the rural domestic architecture of Glenn Murcutt. The results are then discussed in terms of Murcutt's architecture from four perspectives: grammatical transformation of syntax, epistemological questions, similarity or disparity and finally in terms of JPG variations. The findings of this paper suggest that the combined analytic approach facilitates the exploration of both the grammatical and syntactical genotypes of sets of architectural designs.
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FREDDO, ADEMIR ROBERTO, and CESAR AUGUSTO TACLA. "POAM: PARTIAL ALIGNMENT OF ONTOLOGIES IN DIALOG OF AGENTS BASED ON CONCEPT SIMILARITY." International Journal of Semantic Computing 04, no. 03 (2010): 357–84. http://dx.doi.org/10.1142/s1793351x10001048.
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This paper describes a method to partially align ontologies in dialogs of agents which use different ontologies. The method aims at aligning in execution time only the concepts necessary to the agents fulfill the current dialog. Thus, reducing the number of concepts to be searched in the target ontology is a very important requirement for agents' mutual understanding. The proposed method (named POAM, acronym for Partial Ontology Alignment Method) uses syntactical and linguistic techniques to group concepts together. The underlying rationale of POAM is that a person perceives an object and immediately identifies some properties. Even never before seen objects can be interpreted independently of any class, because properties in the real world exist independently of any class. Hence, similarity between a pair of concepts is calculated based on the similarity of their properties. A set of measures including syntactical, structural and semantic ones are used to calculate similarity between the properties associated to the concepts. A property signature vector is created for each concept and the similarity between two concepts is given by the distance between the corresponding vectors in a high dimensional space. We demonstrate that POAM reduces the number of candidate mappings when aligning concepts in a dialog of agents by means of an evaluation using ontologies from the bibliographic domain of the Ontology Alignment Evaluation Initiative (OAEI). We also show that POAM performs satisfactorily well considering the quality of results measured with the precision and recall metrics.
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Banawan, Michelle P., Jinnie Shin, Tracy Arner, Renu Balyan, Walter L. Leite, and Danielle S. McNamara. "Shared Language: Linguistic Similarity in an Algebra Discussion Forum." Computers 12, no. 3 (2023): 53. http://dx.doi.org/10.3390/computers12030053.
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Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies, and similarities in how they construe and communicate meaning. This study examines the extent to which discourse reveals “shared language” among its participants that can promote inclusion or affinity. Shared language is characterized in terms of linguistic features and lexical, syntactical, and semantic similarities. We leverage a multi-method approach, including (1) feature engineering using state-of-the-art natural language processing techniques to select the most appropriate features, (2) the bag-of-words classification model to predict linguistic similarity, (3) explainable AI using the local interpretable model-agnostic explanations to explain the model, and (4) a two-step cluster analysis to extract innate groupings between linguistic similarity and emotion. We found that linguistic similarity within and between the threaded discussions was significantly varied, revealing the dynamic and unconstrained nature of the discourse. Further, word choice moderately predicted linguistic similarity between posts within threaded discussions (accuracy = 0.73; F1-score = 0.67), revealing that discourse participants’ lexical choices effectively discriminate between posts in terms of similarity. Lastly, cluster analysis reveals profiles that are distinctly characterized in terms of linguistic similarity, trust, and affect. Our findings demonstrate the potential role of linguistic similarity in supporting social cohesion and affinity within online discourse communities.
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Yudistira, Renaldy Serby, and Ruswan Dallyono. "Linguistic Features and English Interference on Bahasa Indonesia Usage among Indonesian TikTok Users." NOBEL: Journal of Literature and Language Teaching 15, no. 1 (2024): 50–65. http://dx.doi.org/10.15642/nobel.2024.15.1.50-65.
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The development of English in Indonesia has increased rapidly. Many people learn English both through formal and non-formal education. However, this widespread exposure has also resulted in language interference, particularly when engaging on social media. This interference poses a potential shift in the features of Bahasa Indonesia as the national language. To investigate this issue, this study is designed to explore linguistic features affected by language interference and factors contributing to such language interference on TikTok, specifically among Indonesian TikTok users. To employ a qualitative research approach, data were obtained from post and comment sections of Indonesian TikTok users. The data were analyzed using Chaer and Agustina’s (2004) theory, which divided language interference into four types: lexical, syntactical, morphological, and phonological. Based on that theory, this study reveals that four linguistic features experienced language interference on TikTok: lexical (63%), syntactical (10%), morphological (22%), and phonological (5%). This study indicates three factors causing language interference in Indonesian TikTok users: language similarity, language contact, and terms of technological development. This research highlights the linguistic phenomenon of social media discourse in Indonesia.
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KOÇOĞLU, Turgut. "Similarity Between Commentator Şem'î Şem'ullah's Method Of Interpretation For Mesnevî And Walter G. Andrews's Syntactical Text Interpretation." Journal of Turkish Studies Volume 7 Issue 4-II, no. 7 (2012): 2249–58. http://dx.doi.org/10.7827/turkishstudies.4021.
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Belhajjame, Khalid, and Marco Brambilla. "Ontological Description and Similarity-Based Discovery of Business Process Models." International Journal of Information System Modeling and Design 2, no. 2 (2011): 47–66. http://dx.doi.org/10.4018/jismd.2011040103.
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Project repositories are a central asset in software development, as they preserve the knowledge gathered in past development activities. Locating relevant information in a vast project repository is problematic, because it requires manually tagging projects with accurate metadata, an activity which is time consuming and prone to errors and omissions. Just like any other artifact or web service, business processes can be stored in repositories to be shared and used by third parties, e.g., as building blocks for constructing new business processes. The success of such a paradigm depends partly on the availability of effective search tools to locate business processes that are relevant to the user purposes. A handful of researchers have investigated the problem of business process discovery using as input syntactical and structural information that describes business processes. This work explores an additional source of information encoded in the form of annotations that semantically describe business processes. Business processes can be semantically described using the so called abstract business processes. These are designated by concepts from an ontology which additionally captures their relationships. This ontology can be built in an automatic fashion from a collection of (concrete) business processes, and this work illustrates how it can be refined by domain experts and used in the discovery of business processes, with the purpose of reuse and increase in design productivity.
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Yeshkeyev, A. R., O. I. Ulbrikht, and M. T. Omarova. "Double factorization of the Jonsson spectrum." BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS 116, no. 4 (2024): 185–96. https://doi.org/10.31489/2024m4/185-196.
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First of all, we have to note that in this article, we introduced the new concepts of relations between Jonsson theories in the class of cosemanticness for some considered Jonsson spectrum. All consideration of this new approach was done under sufficiently important class of Jonsson theories, which we called as normal Jonsson theories class. The main result, that we obtained, describes the model-theoretical properties of syntactical and semantical similarities inside the fixed cosemanticness class. For all new concepts in the article, we provided classical samples. The main result of this paper is considering normal Jonsson theories class by similarity to some fixed class of polygons (S-acts).
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Otman, Maarouf, El Ayachi Rachid, and Biniz Mohamed. "Realization of an intelligent evaluation system." International Journal of Informatics and Communication Technology 12, no. 3 (2023): 284–92. https://doi.org/10.11591/ijict.v12i3.pp284-292.
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A number of benefits have been reported for computer-based assessments over traditional paper-based exams, both in terms of IT support for question development, reduced distribution and test administration costs, and automated support. Possible for the ranking. However, existing computerized assessment systems do not provide all kinds of questions, namely open questions that require writing solutions. To overcome the challenges of the existing, the objective of this work is to achieve an intelligent evaluation system (IES) responding to the problems identified, and which adapts to the different types of questions, especially open-ended questions of which the answer requires sentence writing or programming.
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Oliveira, Kleinner, Karin Breitman, and Toacy Oliveira. "A Flexible Strategy-Based Model Comparison Approach: Bridging the Syntactic and Semantic Gap." JUCS - Journal of Universal Computer Science 15, no. (11) (2009): 2225–53. https://doi.org/10.3217/jucs-015-11-2225.
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In this paper we discuss the importance of model comparison as one of the pillars of model-driven development (MDD). We propose an innovative, flexible, model comparison approach, based on the composition of matching strategies. The proposed approach is fully implemented by a match operator that combines syntactical matching rule, synonym dictionary and typographic similarity strategies to a semantic, ontology-based strategy. Ontologies are semantically richer, have greater power of expression than UML models and can be formally verified for consistency, thus providing more reliability and accuracy to model comparison. The proposed approach is presented in the format of a workflow that provides clear guidance to users and facilitates the inclusion of new matching strategies and evolution.
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Ban Kirigin, Tajana, Sanda Bujačić Babić, and Benedikt Perak. "Lexical Sense Labeling and Sentiment Potential Analysis Using Corpus-Based Dependency Graph." Mathematics 9, no. 12 (2021): 1449. http://dx.doi.org/10.3390/math9121449.
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This paper describes a graph method for labeling word senses and identifying lexical sentiment potential by integrating the corpus-based syntactic-semantic dependency graph layer, lexical semantic and sentiment dictionaries. The method, implemented as ConGraCNet application on different languages and corpora, projects a semantic function onto a particular syntactical dependency layer and constructs a seed lexeme graph with collocates of high conceptual similarity. The seed lexeme graph is clustered into subgraphs that reveal the polysemous semantic nature of a lexeme in a corpus. The construction of the WordNet hypernym graph provides a set of synset labels that generalize the senses for each lexical cluster. By integrating sentiment dictionaries, we introduce graph propagation methods for sentiment analysis. Original dictionary sentiment values are integrated into ConGraCNet lexical graph to compute sentiment values of node lexemes and lexical clusters, and identify the sentiment potential of lexemes with respect to a corpus. The method can be used to resolve sparseness of sentiment dictionaries and enrich the sentiment evaluation of lexical structures in sentiment dictionaries by revealing the relative sentiment potential of polysemous lexemes with respect to a specific corpus. The proposed approach has the potential to be used as a complementary method to other NLP resources and tasks, including word disambiguation, domain relatedness, sense structure, metaphoricity, as well as a cross- and intra-cultural discourse variations of prototypical conceptualization patterns and knowledge representations.
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Fredsted, Elin. "Schleswig – a region of longitudinal language contact." Globe: A Journal of Language, Culture and Communication 15 (October 18, 2023): 4–21. http://dx.doi.org/10.54337/ojs.globe.v15i.8035.
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The topic of this article is the structural similarity of neighbouring language varieties belonging to two different branches of the Germanic languages. The German-Danish border region (Schleswig/Sønderjylland) is characterized by longitudinal language contact between West and North Germanic varieties, which have developed common features not to be found in other varieties of these languages spoken outside the contact area. These shared features are the results of regional multilingualism, language contact, and/or of language shift(s). This paper focuses on syntactical convergences. Examples of different aspects of convergences are presented, covering mainly convergences from the North Germanic regional language of South Jutish to West Germanic varieties (Low German, North Frisian, and Standard German regiolect), and from Standard German to the Standard Danish variety spoken by members of the Danish minority on the German side of the border since 1920.
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Pais, Sebastião, and Gaël Dias. "Asymmetric Attributional Word Similarity Measures to Detect the Relations of Textual Generality." Computers 9, no. 4 (2020): 81. http://dx.doi.org/10.3390/computers9040081.
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In this work, we present a new unsupervised and language-independent methodology to detect the relations of textual generality. For this, we introduce a particular case of Textual Entailment (TE), namely Textual Entailment by Generality (TEG). TE aims to capture primary semantic inference needs across applications in Natural Language Processing (NLP). Since 2005, in the TE Recognition (RTE) task, systems have been asked to automatically judge whether the meaning of a portion of the text, the Text (T), entails the meaning of another text, the Hypothesis (H). Several novel approaches and improvements in TE technologies demonstrated in RTE Challenges are signaling renewed interest towards a more in-depth and better understanding of the core phenomena involved in TE. In line with this direction, in this work, we focus on a particular case of entailment, entailment by generality, to detect the relations of textual generality. In text, there are different kinds of entailments, yielded from different types of implicative reasoning (lexical, syntactical, common sense based), but here, we focus just on TEG, which can be defined as an entailment from a specific statement towards a relatively more general one. Therefore, we have T→GH whenever the premise T entails the hypothesis H, this also being more general than the premise. We propose an unsupervised and language-independent method to recognize TEGs, from a pair ⟨T,H⟩ having an entailment relation. To this end, we introduce an Informative Asymmetric Measure (IAM) called Simplified Asymmetric InfoSimba (AISs), which we combine with different Asymmetric Association Measures (AAM). In this work, we hypothesize about the existence of a particular mode of TE, namely TEG. Thus, the main contribution of our study is highlighting the importance of this inference mechanism. Consequently, the new annotation data seem to be a valuable resource for the community.
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Gagarina, Natalia Vladimirovna. ""The hare hugs the rabbit. He is white ... Who is white?": Pronominal anaphora in Russian." ZAS Papers in Linguistics 48 (January 1, 2007): 139–70. http://dx.doi.org/10.21248/zaspil.48.2007.357.
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This paper investigates the production and comprehension of intrasentential anaphoric pronominal reference in Russian. In particular, it examines the elicited imitation and comprehension of three anaphoric pronouns in subject position – personal 3rd singular masculine, demonstrative and zero – in one hundred and eighty monolingual Russian-speaking children and twenty adults. The three types of pronouns were designed to have an antecedent in the preceding sentence containing a verb and two arguments. These antecedents differ in their syntactical role and animacy. The sentence position, agentivity and topicality remained constant. The sentences with (in)animate subjects and objects constituted the following four 'conditions': two sentences with a subject and an object being either animate or inanimate and two sentences with a subject and an object exhibiting a diverse (in)animacy. Regarding the resolution of the anaphoric pronouns the similarity principle (or feature-concord rule) and its possible violations were tested. This principle suggests that an anaphoric pronoun is most likely resolved to the antecedent with a maximum of similar characteristics or features and it primarily governs the assignment of an antecedent to anaphoric pronouns in subject position in the absence of the violating conditions. Results show the influence of this rule on the anaphora resolution process increasing with age, on the one hand, and the development of the impact of animacy, syntactic role and the type of anaphoric pronouns that violate the feature-concord rule, on the other.
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Halii, L. H. "Typological structure as a Model to Study Languages in Contrast." Scientific Journal of National Pedagogical Dragomanov University. Series 9. Current Trends in Language Development, no. 18 (March 18, 2019): 46–60. http://dx.doi.org/10.31392/npu-nc.series9.2018.18.04.
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The article studies the typological system of languages belonging to Indo-European language family and the influence of native language interference on creative written productions of English language learners. It has been defined that the components of linguistic complexity in writing follow different developmental trajectories related to different levels of language proficiency, interference being observed not only throughout closely related languages. Based on this assumption linguistic complexity has been studied in the aspect of the native language transfer and the languages have been classified according to the typological similarity of language patterns but not according to language family relation. It has been proved that typologically similar languages belonging to the same language group or family cause the same mistakes in the process of ESL studying, specifically while producing complex speech structures. The last stage of the research involves the analysis of the native language influence on English creative written productions depending on the proficiency level of the producer. Finally, languages have been classified into clusters which have the same characteristics (morphological and syntactical) in their influence on ESL studying and a new model to study language interference in contrast has been proposed.
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ROCHIMAH, SITI, WAN M. N. WAN KADIR, and ABDUL H. ABDULLAH. "UTILIZING MULTIFACETED REQUIREMENT TRACEABILITY APPROACH: A CASE STUDY." International Journal of Software Engineering and Knowledge Engineering 21, no. 04 (2011): 571–603. http://dx.doi.org/10.1142/s0218194011005372.
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Software evolution is inevitable. When a system evolves, there are certain relationships among software artifacts that must be maintained. Requirement traceability is one of the important factors in facilitating software evolution since it maintains the artifacts relationship before and after a change is performed. Requirement traceability can be expensive activities. Many researchers have addressed the problem of requirement traceability, especially to support software evolution activities. Yet, the evaluation results of these approaches show that most of them typically provide only limited support to software evolution. Based on the problems of requirement traceability, we have identified three directions that are important for traceability to support software evolution, i.e. process automation, procedure simplicity, and best results achievement. Those three directions are addressed in our multifaceted approach of requirement traceability. This approach utilizes three facets to generate links between artifacts, i.e. syntactical similarity matching, link prioritization, and heuristic-list based processes. This paper proposes the utilization of multifaceted approach to traceability generation and recovery in facilitating software evolution process. The complete experiment has been applied in a real case study. The results show that utilization of these three facets in generating the traceability among artifacts is better than the existing approach, especially in terms of its accuracy.
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Feng, Yue, and Ebrahim Bagheri. "Methods and resources for computing semantic relatedness." Encyclopedia with Semantic Computing and Robotic Intelligence 01, no. 01 (2017): 1630005. http://dx.doi.org/10.1142/s2425038416300056.
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Semantic relatedness (SR) is defined as a measurement that quantitatively identifies some form of lexical or functional association between two words or concepts based on the contextual or semantic similarity of those two words regardless of their syntactical differences. Section 1 of the entry outlines the working definition of SR and its applications and challenges. Section 2 identifies the knowledge resources that are popular among SR methods. Section 3 reviews the primary measurements used to calculate SR. Section 4 reviews the evaluation methodology which includes gold standard dataset and methods. Finally, Sec. 5 introduces further reading. In order to develop appropriate SR methods, there are three key aspects that need to be examined: (1) the knowledge resources that are used as the source for extracting SR; (2) the methods that are used to quantify SR based on the adopted knowledge resource; and (3) the datasets and methods that are used for evaluating SR techniques. The first aspect involves the selection of knowledge bases such as WordNet or Wikipedia. Each knowledge base has its merits and downsides which can directly affect the accuracy and the coverage of the SR method. The second aspect relies on different methods for utilizing the beforehand selected knowledge resources, for example, methods that depend on the path between two words, or a vector representation of the word. As for the third aspect, the evaluation for SR methods consists of two aspects, namely (1) the datasets that are used and (2) the various performance measurement methods. SR measures are increasingly applied in information retrieval to provide semantics between query and documents to reveal relatedness between non-syntactically-related content. Researchers have already applied many different information and knowledge sources in order to compute SR between two words. Empirical research has already shown that results of many of these SR techniques have reasonable correlation with human subjects interpretation of relatedness between two words.
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Sychandone, Nokthavivanh. "COMPARATIVE ERROR ANALYSIS IN ENGLISH WRITING BY FIRST, SECOND, AND THIRD YEAR STUDNETS OF ENGLISH DEPARTMENT OF FACULTY OF EDUCATION AT CHAMPASACK UNIVERSITY." Jurnal Penelitian Humaniora 17, no. 1 (2016): 74. http://dx.doi.org/10.23917/humaniora.v17i1.2353.
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levels. To investigate the error types, the frequency of error types, the similarities and difference of errors and the last to find the error sources that occur in first, second and third year learners. Error analysis is one type of linguistic study and it focuses on learners’ error making. The linguistic category and surface strategy taxonomy are used to find out the types of error. The analysis the phenomenon based on Brown (1980) namely, error identification, error classification, Error description and error explanation. The data from students’ writing products, 54 pieces in three levels andthe total errors are 571 erroneous sentences. There are two types of errors, namely lexical errors and syntactical errors; eight error categories and twenty-seven error cases. The second year learners made the most error 263 errors or 46, 05% whilefirst year learners produced 229 errors or 40, 10% and third year learners made 79 errors or 13, 83%. There are similarity in errors types, five similar categories and five error cases, but there are three different error categories and eighteen error cases. The main error sources, learners had lack knowledge of English grammatical rule. The overgeneralization (265 errors or 46, 40%) influences learners’ error, language transfer (199 errors or 34, 85%) still interfere learners’ acquisition and simplification (107 errors or 18, 73%) is one factor that effect learners’ errors.
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Chakraborty, Tanmoy, Dipankar Das, and Sivaji Bandyopadhyay. "Identifying Bengali Multiword Expressions using semantic clustering." Lingvisticæ Investigationes. International Journal of Linguistics and Language Resources 37, no. 1 (2014): 106–28. http://dx.doi.org/10.1075/li.37.1.04cha.
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One of the key issues in both natural language understanding and generation is the appropriate processing of Multiword Expressions (MWEs). MWEs pose a huge problem to the precise language processing due to their idiosyncratic nature and diversity in lexical, syntactical and semantic properties. The semantics of a MWE cannot be expressed after combining the semantics of its constituents. Therefore, the formalism of semantic clustering is often viewed as an instrument for extracting MWEs especially for resource constraint languages like Bengali. The present semantic clustering approach contributes to locate clusters of the synonymous noun tokens present in the document. These clusters in turn help measure the similarity between the constituent words of a potentially candidate phrase using a vector space model and judge the suitability of this phrase to be a MWE. In this experiment, we apply the semantic clustering approach for noun-noun bigram MWEs, though it can be extended to any types of MWEs. In parallel, the well known statistical models, namely Point-wise Mutual Information (PMI), Log Likelihood Ratio (LLR), Significance function are also employed to extract MWEs from the Bengali corpus. The comparative evaluation shows that the semantic clustering approach outperforms all other competing statistical models. As a byproduct of this experiment, we have started developing a standard lexicon in Bengali that serves as a productive Bengali linguistic thesaurus.
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Spranzi, Marta. "Galileo and the Mountains of the Moon: Analogical Reasoning, Models and Metaphors in Scientific Discovery." Journal of Cognition and Culture 4, no. 3-4 (2004): 451–83. http://dx.doi.org/10.1163/1568537042484904.
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AbstractThis paper is about the use of analogical reasoning, models and metaphors in Galileo's discovery of the mountains of the moon, which he describes in the Starry Messenger, a short but groundbreaking treatise published in 1610. On the basis of the observations of the Moon he has made with the newly invented telescope, Galileo shows that the Moon has mountains and that therefore it shares the same solid, opaque and rugged nature of the Earth. I will first reconstruct Galileo's reasoning, and illustrate the counterintuitive and quasi-circular way in which discovery depends on analogy: in order for analogical reasoning to succeed in bridging ontological gaps and thus serve as a discovery tool, a certain similarity between what are considered as radically different domains has to be presupposed. More particularly, in order for analogical reasoning to lead to genuine discoveries, salient features have to be selected in the source domain that will be mapped onto the target domain. There is disagreement as to how this mapping is successfully carried out: the syntactical (Dedre Gentner), pragmatic (Paul Thagard) and ontological-categorical (Rom Harré) approaches, all illuminate some features of this selection in the mapping process. On the basis of an analysis of Galileo's discovery, I will argue that we need a different "bootstrapping" approach which involves the construction of an imaginary temporary model encompassing both the source and the target domains, and which is occasionally strengthened by metaphors which serve as incomplete transitional models.
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Jian, Zhongquan, Yanhao Chen, Jiajian Li, et al. "SimRP: Syntactic and Semantic Similarity Retrieval Prompting Enhances Aspect Sentiment Quad Prediction." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 23 (2025): 24248–56. https://doi.org/10.1609/aaai.v39i23.34601.
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Aspect Sentiment Quad Prediction (ASQP) is the most complex subtask of Aspect-based Sentiment Analysis (ABSA), aiming to predict all sentiment quadruples within the given sentence. Due to the complexity of sentence syntaxes and the diversity of sentiment expressions, generative methods gradually become the mainstream approach in ASQP. However, existing generative models are constrained in the effectiveness of demonstrations. Semantically similar demonstrations help in judging sentiment categories and polarities but may confuse the model in recognizing aspect and opinion terms, which are more related to sentence syntaxes. To this end, we first develop Syn2Vec, a method for calculating syntactic vectors to support the retrieval of syntactically similar demonstrations. Then, we propose Syntactic and Semantic Similarity Retrieval Prompting (SimRP) to construct effective prompts by retrieving the most related demonstrations that are syntactically and semantically similar. With these related demonstrations, pre-trained generative models, especially Large Language Models (LLMs), can fully release their potential to recognize sentiment quadruples. Extensive experiments in Supervised Fine-Tuning (SFT) and In-context Learning (ICL) paradigms demonstrate the effectiveness of SimRP. Furthermore, we find that LLMs' capabilities in ASQP are severely underestimated by biased data annotations and the exact matching metric. We propose a novel constituent subtree-based fuzzy metric for more accurate and rational quadruple recognition.
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Nazarov, Nazarii. "PROSODY OF KYIVAN RUSʼ CHRONICLES: STROPHIC STRUCTURE OF OLD KYIVAN POETRY (episode about the origin of Rusʼ)". MOVOZNAVSTVO 328, № 1 (2023): 52–79. http://dx.doi.org/10.33190/0027-2833-328-2023-1-004.
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The article introduces a new research tool for studying the prosodic and metric structure of Kyiv Rus chronicles and other texts — a strophic period. Strophic period was a metrical, lexical and syntactical unit with a symmetrical structure. On the lexical level, the symmetry was expressed by symmetrically repeated lexical series, whereas on the metrical — by the equal quantity of syllables in the two halves of the strophic period, i.e. stroph and antistroph. The notion of symmetrical lexical series was a lacking chain to integrate the study of the chronicles and «Slovo o polku Igoreve» into one methodological frame, and to unify different ideas expressed previously about the nature of prosodic structure of the «Slovo o polku Igoreve». Strophic period of the Kyiv Rus chronicles shares a lot of elements in its formal structure with the strophic organisation of Old Czech «Dalimil Chronicle». This implies that the formal structure of the both monuments should have had some common source that predated the both, probably, it was byzantine hymnography. Such a relationship is supported by the similarity of metrical and lexical models in Byzantine hymnography (in particular, in the kondaks of Romanos Melodos) and in both Slavic monuments. The proposed tools of metrical analysis are used in the article to divide the opening episode of the Tale of Bygone Years according to the Ypatian copy into metrical segments (strophic periods). It turned out that the manuscript transmission in all the oldest manuscripts (Lavrentian, Ypatian, Radziviloan, Ostroh) consistently preserved the division into cola, which are grouped into larger units — lines and strophic periods. The author of this individual episode was aware of the form in which he created, as evidenced by the use of strophic periods of different lengths as a means of distinguishing compositional parts. Thus, folklore sources could influence this complex poetic form only as models for certain lexical formulas that were subordinated to already known literary models.
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Gali, Najlah, Radu Mariescu-Istodor, Damien Hostettler, and Pasi Fränti. "Framework for syntactic string similarity measures." Expert Systems with Applications 129 (September 2019): 169–85. http://dx.doi.org/10.1016/j.eswa.2019.03.048.
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Yeshkeyev, A. R., O. I. Ulbrikht, and G. A. Urken. "Similarities of Jonsson spectra’s classes." BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS 112, no. 4 (2023): 130–43. http://dx.doi.org/10.31489/2023m4/130-143.
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The study of syntactic and semantic properties of a first-order language, generally speaking, for incomplete theories, is one of the urgent problems of mathematical logic. In this article we study Jonsson theories, which are satisfied by most classical examples from algebra and which, generally speaking, are not complete. A new and relevant method for studying Jonson theories is to study these theories using the concepts of syntactic and semantic similarities. The most invariant concept is the concept of syntactic similarity of theories, because it preserves all the properties of the theories under consideration. The main result of this article is the fact that any perfect Jonson theory which are complete for existential sentences, is syntactically similar to some polygon theory (S-polygon, where S is a monoid). This result extends to the corresponding classes of Jonsson theories from the Jonsson spectrum of an arbitrary model of an arbitrary signature.
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Igaab, Zainab Kadim, and Intisar Raham Tarrad. "Pronouns in English and Arabic: A Contrastive Study." English Language and Literature Studies 9, no. 1 (2019): 53. http://dx.doi.org/10.5539/ells.v9n1p53.
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Pronouns are defined as being one of the parts of speech that obtain their meaning from other noun phrases in a sentence. This study is descriptive, analytic, and contrastive. It deals with comparing pronouns in English and Arabic by concentrating on the points of difference and similarity between the two languages.
 
 This study aims at describing pronouns in both languages and then the comparison is made by defining pronouns, showing their syntactic, semantic, and pragmatic aspects to know to what extent both languages are similar or different in using pronouns.
 
 It is hypothesized that the two languages are similar to each other in terms of their syntactic, semantic, and pragmatic aspects of pronouns; pronouns are found in both languages; and there are some points of similarity and difference between the two languages, but the differences outweigh the similarities. 
 
 English has a clear division of pronouns. Pronouns are dealt with syntactically, semantically and pragmatically. In Arabic the division of pronouns is completely different.
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Lang, Joel, and Mirella Lapata. "Similarity-Driven Semantic Role Induction via Graph Partitioning." Computational Linguistics 40, no. 3 (2014): 633–69. http://dx.doi.org/10.1162/coli_a_00195.
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As in many natural language processing tasks, data-driven models based on supervised learning have become the method of choice for semantic role labeling. These models are guaranteed to perform well when given sufficient amount of labeled training data. Producing this data is costly and time-consuming, however, thus raising the question of whether unsupervised methods offer a viable alternative. The working hypothesis of this article is that semantic roles can be induced without human supervision from a corpus of syntactically parsed sentences based on three linguistic principles: (1) arguments in the same syntactic position (within a specific linking) bear the same semantic role, (2) arguments within a clause bear a unique role, and (3) clusters representing the same semantic role should be more or less lexically and distributionally equivalent. We present a method that implements these principles and formalizes the task as a graph partitioning problem, whereby argument instances of a verb are represented as vertices in a graph whose edges express similarities between these instances. The graph consists of multiple edge layers, each one capturing a different aspect of argument-instance similarity, and we develop extensions of standard clustering algorithms for partitioning such multi-layer graphs. Experiments for English and German demonstrate that our approach is able to induce semantic role clusters that are consistently better than a strong baseline and are competitive with the state of the art.
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Boyle, Robyn, and Veronika Coltheart. "Effects of Irrelevant Sounds on Phonological Coding in Reading Comprehension and Short term Memory." Quarterly Journal of Experimental Psychology Section A 49, no. 2 (1996): 398–416. http://dx.doi.org/10.1080/713755630.
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The effects of irrelevant sounds on reading comprehension and short-term memory were studied in two experiments. In Experiment 1, adults judged the acceptability of written sentences during irrelevent speech, accompanied and unaccompanied singing, instrumental music, and in silence. Sentences varied in syntactic complexity: Simple sentences contained a right-branching relative clause ( The applause pleased the woman that gave the speech) and syntactically complex sentences included a centre-embedded relative clause ( The hay that the farmer stored fed the hungry animals). Unacceptable sentences either sounded acceptable ( The dog chased the cat that eight up all his food) or did not ( The man praised the child that sight up his spinach). Decision accuracy was impaired by syntactic complexity but not by irrelevant sounds. Phonological coding was indicated by increased errors on unacceptable sentences that sounded correct. These error rates were unaffected by irrelevant sounds. Experiment 2 examined effects of irrelevant sounds on ordered recall of phonologically similar and dissimilar word lists. Phonological similarity impaired recall. Irrelevant speech reduced recall but did not interact with phonological similarity. The results of these experiments question assumptions about the relationship between speech input and phonological coding in reading and the short-term store.
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Pakray, Partha, Sivaji Bandyopadhyay, and Alexander Gelbukh. "Textual Entailment Using Lexical And Syntactic Similarity." International Journal of Artificial Intelligence & Applications 2, no. 1 (2011): 43–58. http://dx.doi.org/10.5121/ijaia.2011.2104.
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Jing, Xiong, Liu Yun-Tong, and Yuan Dong. "Dependency Syntactic Tree Supported Sentence Similarity Computing." Information Technology Journal 12, no. 20 (2013): 5685–88. http://dx.doi.org/10.3923/itj.2013.5685.5688.
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Gordon, Peter C., Randall Hendrick, and William H. Levine. "Memory-Load Interference in Syntactic Processing." Psychological Science 13, no. 5 (2002): 425–30. http://dx.doi.org/10.1111/1467-9280.00475.
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Participants remembered a short set of words while reading syntactically complex sentences (object-extracted clefts) and syntactically simpler sentences (subject-extracted clefts) in a memory-load study. The study also manipulated whether the words in the set and the words in the sentence were of matched or unmatched types (common nouns vs. proper names). Performance in sentence comprehension was worse for complex sentences than for simpler sentences, and this effect was greater when the type of words in the memory load matched the type of words in the sentence. These results indicate that syntactic processing is not modular, instead suggesting that it relies on working memory resources that are used for other nonsyntactic processes. Further, the results indicate that similarity-based interference is an important constraint on information processing that can be overcome to some degree during language comprehension by using the coherence of language to construct integrated representations of meaning.
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Zhou, Ya, Cheng Li, Guimin Huang, Qingkai Guo, Hui Li, and Xiong Wei. "A Short-Text Similarity Model Combining Semantic and Syntactic Information." Electronics 12, no. 14 (2023): 3126. http://dx.doi.org/10.3390/electronics12143126.
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As one of the prominent research directions in the field of natural language processing (NLP), short-text similarity has been widely used in search recommendation and question-and-answer systems. Most of the existing short textual similarity models focus on considering semantic similarity while overlooking the importance of syntactic similarity. In this paper, we first propose an enhanced knowledge language representation model based on graph convolutional networks (KEBERT-GCN), which effectively uses fine-grained word relations in the knowledge base to assess semantic similarity and model the relationship between knowledge structure and text structure. To fully leverage the syntactic information of sentences, we also propose a computational model of constituency parse trees based on tree kernels (CPT-TK), which combines syntactic information, semantic features, and attentional weighting mechanisms to evaluate syntactic similarity. Finally, we propose a comprehensive model that integrates both semantic and syntactic information to comprehensively evaluate short-text similarity. The experimental results demonstrate that our proposed short-text similarity model outperforms the models proposed in recent years, achieving a Pearson correlation coefficient of 0.8805 on the STS-B dataset.
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Gamallo, Pablo. "Compositional Distributional Semantics with Syntactic Dependencies and Selectional Preferences." Applied Sciences 11, no. 12 (2021): 5743. http://dx.doi.org/10.3390/app11125743.
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This article describes a compositional model based on syntactic dependencies which has been designed to build contextualized word vectors, by following linguistic principles related to the concept of selectional preferences. The compositional strategy proposed in the current work has been evaluated on a syntactically controlled and multilingual dataset, and compared with Transformer BERT-like models, such as Sentence BERT, the state-of-the-art in sentence similarity. For this purpose, we created two new test datasets for Portuguese and Spanish on the basis of that defined for the English language, containing expressions with noun-verb-noun transitive constructions. The results we have obtained show that the linguistic-based compositional approach turns out to be competitive with Transformer models.
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Korbozerova, Nina. "SPANISH AND UKRAINIAN SYNTACTIC TYPE (SIMILARITIES AND DIFFERENCES)." PROBLEMS OF SEMANTICS, PRAGMATICS AND COGNITIVE LINGUISTICS, no. 35 (2019): 37–44. http://dx.doi.org/10.17721/2663-6530.2019.35.03.
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The Indo-European syntactic system is very stable. This explains the fact that the Spanish and the Ukrainian, originating from a unique linguistic base, in their syntactic structure have a considerable number of common features. The syntactic similarity of comparative languages is manifested of the group of words, sentences and their elements. According to the classification criteria in the languages above mentioned there are a lot of syntactic similarities: are distinguished similar sentence members which are expressed by similar morphological modes. In both languages the order of the words in the sentence are very similar too. Both investigated languages are characterized by the common modes of expression of syntactic relationships and by similar links in word groups. The structure of simple and compound sentences also seems in both languages. Also there are simple and compound sentences, which are subdivided into coordinated and subordinated ones. On the other hand, each of the compared languages has its own distinctive features of the formal, semantic and functional deep level, which is explained by the specific national character of each of the studied languages. In the comparative languages, the group of words, as a succession of two or more significant words linked semantically and grammatically, represents the complex denomination of the phenomena of the reality. It is one of the very important syntactic units, with which we can build the sentences. In both languages there are a lot of isomorphic characters referring to groups of words. In relation to the degree of fusion of its components, the groups of words can be free or fixed. Thus in the groups of free words the lexical meanings of their constituents are conserved. They differ from the fixed ones whose components lose their lexical dependence. The fixed groups are divided into the dependents syntactically and phraseologically. In the comparative languages, the dependent groups syntactically perform a unique syntactic function. They do not split, one of its components is relaxed lexically. The complex character of groups of words can be achieved isomorphically in a similar way: by the amplification of the simple group with a dependent word, by the unification of the nucleus by a simple dependent group, by means of two grammatically dependent elements, by the extension of the direct object.
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Kang, Qiao, Jing Kan, Fangyan Dong, and Kewei Chen. "Semantic Similarity Analysis via Syntax Dependency Structure and Gate Recurrent Unit." Journal of Advanced Computational Intelligence and Intelligent Informatics 28, no. 1 (2024): 179–85. http://dx.doi.org/10.20965/jaciii.2024.p0179.
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Sentences are composed of words, phrases, and clauses. The relationship between them is usually tree-like. In the hierarchical structure of the sentence, the dependency relationships between different components affect the syntactic structure. Syntactic structure is very important for understanding the meaning of the whole sentence. However, the gated recursive unit (GRU) models cannot fully encode hierarchical syntactic dependencies, which leads to its poor performance in various natural language tasks. In this paper, a model called relative syntactic distance bidirectional gated recursive unit (RSD-BiGRU) is constructed to capture syntactic structure dependencies. The model modifies the gating mechanism in GRU through relative syntactic distance. It also offers a transformation gate to model the syntactic structure more directly. Embedding sentence meanings with sentence structure dependency into dense vectors. This model is used to conduct semantic similarity experiments on the QQP and SICK datasets. The results show that the sentence representation obtained by RSD-BiGRU model contains more semantic information. This is helpful for semantic similarity analysis tasks.
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Urken, G. A. "Syntactic similarity of definable closures of Jonsson sets." BULLETIN OF THE KARAGANDA UNIVERSITY-MATHEMATICS 90, no. 2 (2018): 119–23. http://dx.doi.org/10.31489/2018m2/119-123.
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Jumarie, Guy. "Informational similarity of graphs in syntactic pattern recognition." Pattern Recognition Letters 15, no. 12 (1994): 1177–81. http://dx.doi.org/10.1016/0167-8655(94)90107-4.
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Li, Xiao, and Qingsheng Li. "Calculation of Sentence Semantic Similarity Based on Syntactic Structure." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/203475.
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Combined with the problem of single direction of the solution of the existing sentence similarity algorithms, an algorithm for sentence semantic similarity based on syntactic structure was proposed. Firstly, analyze the sentence constituent, then through analysis convert sentence similarity into words similarity on the basis of syntactic structure, then convert words similarity into concept similarity through words disambiguation, and, finally, realize the semantic similarity comparison. It also gives the comparison rules in more detail for the modifier words in the sentence which also have certain contributions to the sentence. Under the same test condition, the experiments show that the proposed algorithm is more intuitive understanding of people and has higher accuracy.
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Kim, Dong Kwan. "Enhancing code clone detection using control flow graphs." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3804. http://dx.doi.org/10.11591/ijece.v9i5.pp3804-3812.
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Code clones are syntactically or semantically equivalent code fragments of source code. Copy-and-paste programming allows software developers to improve development productivity, but it could produce code clones that can introduce non-trivial difficulties in software maintenance. In this paper, a code clone detection framework is presented with a feature extractor and a clone classifier using deep learning. The clone classifier is trained with true and false clones and then is tested with a test dataset to evaluate the performance of the proposed approach to clone detection. In particular, the proposed approach to clone detection uses Control Flow Graphs (CFGs) to extract features of a given code snippet. The selected features are used to compute similarity scores for comparing two code fragments. The clone classifier is trained and tested with similarity scores that quantify the degree of how similar two code fragments are. The experimental results demonstrate that using CFG features is a viable methodology in terms of the effectiveness of clone detection for both syntactic and semantic clones.
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Dong, Kwan Kim. "Enhancing code clone detection using control flow graphs." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 3804–12. https://doi.org/10.11591/ijece.v9i5.pp3804-3812.
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Code clones are syntactically or semantically equivalent code fragments of source code. Copy-and-paste programming allows software developers to improve development productivity, but it could produce code clones that can introduce non-trivial difficulties in software maintenance. In this paper, a code clone detection framework is presented with a feature extractor and a clone classifier using deep learning. The clone classifier is trained with true and false clones and then is tested with a test dataset to evaluate the performance of the proposed approach to clone detection. In particular, the proposed approach to clone detection uses Control Flow Graphs (CFGs) to extract features of a given code snippet. The selected features are used to compute similarity scores for comparing two code fragments. The clone classifier is trained and tested with similarity scores that quantify the degree of how similar two code fragments are. The experimental results demonstrate that using CFG features is a viable methodology in terms of the effectiveness of clone detection for both syntactic and semantic clones.
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Luo, Jiajia, Hongtao Shan, Gaoyu Zhang, et al. "Exploiting Syntactic and Semantic Information for Textual Similarity Estimation." Mathematical Problems in Engineering 2021 (January 23, 2021): 1–12. http://dx.doi.org/10.1155/2021/4186750.
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The textual similarity task, which measures the similarity between two text pieces, has recently received much attention in the natural language processing (NLP) domain. However, due to the vagueness and diversity of language expression, only considering semantic or syntactic features, respectively, may cause the loss of critical textual knowledge. This paper proposes a new type of structure tree for sentence representation, which exploits both syntactic (structural) and semantic information known as the weight vector dependency tree (WVD-tree). WVD-tree comprises structure trees with syntactic information along with word vectors representing semantic information of the sentences. Further, Gaussian attention weight is proposed for better capturing important semantic features of sentences. Meanwhile, we design an enhanced tree kernel to calculate the common parts between two structures for similarity judgment. Finally, WVD-tree is tested on widely used semantic textual similarity tasks. The experimental results prove that WVD-tree can effectively improve the accuracy of sentence similarity judgments.
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Little, Claire, David Mclean, Keeley Crockett, and Bruce Edmonds. "A Semantic and Syntactic Similarity Measure for Political Tweets." IEEE Access 8 (2020): 154095–113. http://dx.doi.org/10.1109/access.2020.3017797.
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NINIO, ANAT. "Testing the role of semantic similarity in syntactic development." Journal of Child Language 32, no. 1 (2005): 35–61. http://dx.doi.org/10.1017/s0305000904006713.
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The study explored early syntactic development, and tested the hypothesis that children use similarity of meaning in order to move beyond the learning of individual item-based multiword constructions. The first 6 types of verb–object (VO) constructions in Hebrew-speaking children were analysed for the occurrence of transfer of learning and facilitation, as well as for the semantic similarity of the direct objects (DO). Longitudinal naturalistic speech corpora of 20 children (1;06–2;06) were analysed. We found facilitation (increased rate of learning) among the first 6 types of VO constructions (each type built on a different verb) as evidenced by the accelerating growth curves. Next, we measured the semantic similarity of the DOs using an 8-category system including Patient, Theme and Object of Result. The first 6 DO types represented 3·95 different semantic roles. On the average, after the first VO construction was learned, 3 out of the following 5 constructions produced were not preceded by another VO construction where the DO was of the same semantic category. The results indicate that facilitation of learning of early syntax is most probably NOT mediated by semantic similarity.
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Ferreira, Rafael, Rafael Dueire Lins, Steven J. Simske, Fred Freitas, and Marcelo Riss. "Assessing sentence similarity through lexical, syntactic and semantic analysis." Computer Speech & Language 39 (September 2016): 1–28. http://dx.doi.org/10.1016/j.csl.2016.01.003.
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Yi, Eunkyung, Jean-Pierre Koenig, and Douglas Roland. "Semantic similarity to high-frequency verbs affects syntactic frame selection." Cognitive Linguistics 30, no. 3 (2019): 601–28. http://dx.doi.org/10.1515/cog-2018-0029.
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AbstractThis paper investigates the effect of the high frequency of occurrence of a verb in a syntactic frame on speakers’ selection of that syntactic frame for other verbs. We hypothesize that the frequent co-occurrence of a syntactic frame and a particular verb (what we call an anchor verb) leads to a strong association between the verb and the frame analogous to the relationship between a category and its best exemplar. Our Verb Anchor Hypothesis claims that verbs that are more semantically similar to the anchor are more likely to occur in that syntactic frame than verbs that are less semantically similar to the anchor. We tested the Verb Anchor Hypothesis on the dative alternation which involves the meaning-preserving ditransitive and prepositional frames. A corpus study determined that give was the anchor verb for the ditransitive frame. We then examined whether high semantic similarity to give increases the likelihood of an alternating verb (e.g. to hand) occurring in the ditransitive frame (Mary handed the boy a book) rather than in the prepositional frame (Mary handed a book to the boy). The results of several logistic regression analyses show that semantic similarity to give makes a unique contribution to predicting the choice of the ditransitive frame aside from other factors known to affect syntactic frame selection. Additional analyses suggest that the Verb Anchor Hypothesis might also hold for more narrowly-defined subclasses of alternating verbs.
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Nakamura, Yuki, and Hiroshi Tanaka. "A SEMANTIC METRIC LEARNING APPROACH FOR ENHANCED MALWARE SIMILARITY SEARCH." International Journal of Intelligent Data and Machine Learning 2, no. 01 (2025): 1–7. https://doi.org/10.55640/ijidml-v02i01-01.
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Identifying and categorizing malware variants efficiently is a critical capability for modern cybersecurity systems tasked with defending against rapidly evolving threats. Traditional similarity search techniques often rely on syntactic or signature-based comparisons, which are insufficient for capturing deeper semantic relationships among malware samples, especially in the presence of obfuscation and polymorphism. This research introduces a semantic metric learning approach for enhanced malware similarity search that leverages deep neural embeddings trained to capture high-level behavioral and structural characteristics of malicious code. By employing a supervised metric learning framework with contrastive and triplet loss functions, the model learns a discriminative embedding space in which semantically similar malware instances are mapped closer together while dissimilar samples are pushed farther apart. Experimental evaluations on benchmark malware datasets demonstrate that the proposed method significantly outperforms traditional hashing and signature-based approaches in retrieval precision, recall, and mean average precision. The results underscore the potential of semantic metric learning to advance malware analysis, facilitate threat hunting, and improve incident response workflows by enabling more accurate and scalable similarity-based retrieval.
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Berk-Seligson, Susan. "Linguistic constraints on intrasentential code-switching: A study of Spanish/Hebrew bilingualism." Language in Society 15, no. 3 (1986): 313–48. http://dx.doi.org/10.1017/s0047404500011799.
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ABSTRACTIn recent years, research has increasingly pointed toward the universality of three linguistic constraints on code-switching: (1) an equivalence of structure constraint, (2) a size-of-constituent constraint, and (3) a free morpheme constraint. The evidence derived from this study challenges the universality of the first two of these constraints, and argues instead that their claim to universality is largely a function of the coincidental relative similarity in the syntactic structure of Spanish and English, the two languages upon which most code-switching studies have been based. The present study breaks out of the Spanish-English mold and draws upon data from a language contact situation in which the two languages are syntactically very different from each other, namely, Spanish and Hebrew. The evidence presented also challenges the frequently made assertion that type of code-switching, namely, intra- versus intersentential code-switching, is correlated with degree of bilingualism of the speaker. Finally, the evidence suggests that intrasentential code-switching ability cannot, as some have argued, universally be considered a measure of bilingualism nor a mark of the balanced bilingual. (Code-switching, Spanish, Hebrew, bilingualism, syntactic constraints)
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CHESHIRE, JENNY, and MARIA SECOVA. "The origins of new quotative expressions: the case of Paris French." Journal of French Language Studies 28, no. 2 (2018): 209–34. http://dx.doi.org/10.1017/s0959269518000029.
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ABSTRACTWe analyse genre in the speech of young people with multi-ethnic friendship groups in Paris in order to address the as yet unresolved question of whether new quotatives equivalent in meaning to English BE LIKE result from simultaneous independent parallel developments in languages other than English or from a process of calquing. We conclude that French quotative genre results from independent internal developments, but that it enters the French quotative system in the same way that BE LIKE entered the English system, driven by the meanings of ‘similarity’ or ‘approximation’ that are shared by the lexical item genre in a range of syntactic categories. We propose that in order for a new similarity quotative to emerge, a lexical item with a meaning of ‘similarity’ or ‘approximation’ must become syntactically multifunctional, and that the use of that lexical item must reach a critical frequency threshold. In the case of genre we suggest that the necessary increase in frequency results from the development of the lexical item into a discourse marker. We also analyse another new French quotative, ETRE LA, a sequence that we find is used to highlight activity of many kinds (including, but not confined to, spoken behaviour). The trajectory followed by each of the new quotative expressions conforms to De Smet's proposals about how linguistic innovations spread through the grammar.
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Nenadic, Goran, Irena Spasic, and Sophia Ananiadou. "Mining term similarities from corpora." Recent Trends in Computational Terminology 10, no. 1 (2004): 55–80. http://dx.doi.org/10.1075/term.10.1.04nen.
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In this article, we present an approach to the automatic discovery of term similarities, which may serve as a basis for a number of term-oriented knowledge mining tasks. The method for term comparison combines internal (lexical similarity) and two types of external criteria (syntactic and contextual similarities). Lexical similarity is based on sharing lexical constituents (i.e. term heads and modifiers). Syntactic similarity relies on a set of specific lexico-syntactic co-occurrence patterns indicating the parallel usage of terms (e.g., within an enumeration or within a term coordination/conjunction structure), while contextual similarity is based on the usage of terms in similar contexts. Such contexts are automatically identified by a pattern mining approach, and a procedure is proposed to assess their domain-specific and terminological relevance. Although automatically collected, these patterns are domain dependent and identify contexts in which terms are used. Different types of similarities are combined into a hybrid similarity measure, which can be tuned for a specific domain by learning optimal weights for individual similarities. The suggested similarity measure has been tested in the domain of biomedicine, and some experiments are presented.
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Chen, Baoguo, Yuefang Jia, Zhu Wang, Susan Dunlap, and Jeong-Ah Shin. "Is word-order similarity necessary for cross-linguistic structural priming?" Second Language Research 29, no. 4 (2013): 375–89. http://dx.doi.org/10.1177/0267658313491962.
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This article presents two experiments employing two structural priming paradigms that investigated whether cross-linguistic syntactic priming occurred in Chinese and English passive sentences that differ in word order (production-to-production priming in Experiment 1 and comprehension-to-production priming in Experiment 2). Results revealed that cross-linguistic syntactic priming occurred in Chinese and English passive sentences, regardless of production of primes or comprehension of primes and language direction (L1–L2 or L2–L1). Our findings indicate that word-order similarity between languages is not necessary for cross-linguistic structural priming, supporting the view of a two-stage model of language production.