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Dissertations / Theses on the topic 'Artificial intelligence in language learning'

Author: Grafiati

Published: 7 June 2025

Last updated: 16 July 2025

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1

Babarsad, Omid Bakhshandeh. "Language Learning Through Comparison." Thesis, University of Rochester, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10618060.

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<p> Natural Language Understanding (NLU) has been one of the longest-running and the most challenging areas in artificial intelligence. For any natural language comprehension system having a basic understanding of entities and concepts is a primary requirement. Comparison, where we name the similarities and differences between entities and concepts, is a unique cognitive ability in humans which requires memorizing facts, experiencing things and integration of concepts of the world. Clearly, developing NLU systems that are capable of comprehending comparison is a crucial step forward in AI. In

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2

Panesar, Kulvinder. "Conversational artificial intelligence - demystifying statistical vs linguistic NLP solutions." Universitat Politécnica de Valéncia, 2020. http://hdl.handle.net/10454/18121.

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yes<br>This paper aims to demystify the hype and attention on chatbots and its association with conversational artificial intelligence. Both are slowly emerging as a real presence in our lives from the impressive technological developments in machine learning, deep learning and natural language understanding solutions. However, what is under the hood, and how far and to what extent can chatbots/conversational artificial intelligence solutions work – is our question. Natural language is the most easily understood knowledge representation for people, but certainly not the best for computers beca

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3

Jernite, Yacine. "Learning Representations of Text through Language and Discourse Modeling| From Characters to Sentences." Thesis, New York University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10680744.

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<p> In this thesis, we consider the problem of obtaining a representation of the meaning expressed in a text. How to do so correctly remains a largely open problem, combining a number of inter-related questions (e.g. what is the role of context in interpreting text? how should language understanding models handle compositionality? etc...) In this work, after reflecting on the notion of meaning and describing the most common sequence modeling paradigms in use in recent work, we focus on two of these questions: what level of granularity text should be read at, and what training objectives can le

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4

Shao, Yuanlong. "Learning Sparse Recurrent Neural Networks in Language Modeling." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398942373.

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5

Gulcehre, Caglar. "Two Approaches For Collective Learning With Language Games." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613109/index.pdf.

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Recent studies in cognitive science indicate that language has an important social function. The structure and knowledge of language emerges from the processes of human communication together with the domain-general cognitive processes. Each individual of a community interacts socially with a limited number of peers. Nevertheless societies are characterized by their stunning global regularities. By dealing with the language as a complex adaptive system, we are able to analyze how languages change and evolve over time. Multi-agent computational simulations assist scientists from different disci

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6

Gu, Tianyu. "Shelang : An Implementation of Probabilistic Programming Language and its Applications." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-26016.

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Nowadays, probabilistic models are playing a significant role in various areas in- cluding machine learning, artificial intelligence and cognitive science, etc. How- ever, as those models are becoming more and more complex, it shows that the corresponding programs are really hard to maintain and reuse as well. Meanwhile, the current tools are not feasible enough to enable probabilistic modeling and ma- chine learning to be accessible to the working programmer, who has sufficient do- main expertise, but perhaps not enough expertise in probability theory or machine learning. Probabilistic progra

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7

Cederborg, Thomas. "A Formal Approach to Social Learning: Exploring Language Acquisition Through Imitation." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00937615.

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The topic of this thesis is learning through social interaction, consisting of experiments that focus on word acquisition through imitation, and a formalism aiming to provide stronger theoretical foundations. The formalism is designed to encompass essentially any situation where a learner tries to figure out what a teacher wants it to do by interaction or observation. It groups learners that are interpreting a broad range of information sources under the same theoretical framework. A teachers demonstration, it's eye gaze during a reproduction attempt and a teacher speech comment are all treate

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8

Laugier, Léo. "Analysis and control of online interactions through neural natural language processing." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAT035.

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Le traitement automatique du langage naturel est motivé par des applications où les ordinateurs doivent acquérir une compréhension sémantique et syntaxique du langage humain. Récemment, le domaine a été impacté par un changement de paradigme. Les architectures d'apprentissage profond couplées à des techniques d'apprentissage auto-supervisé sont devenues le cœur des modèles correspondant à l'état de l'art en compréhension et génération du langage naturel. Parfois considérés comme des “foundation models”, ces systèmes ouvrent la voie à de nouveaux cas d'utilisation. Née d'un partenariat académiq

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9

Mahendru, Aroma. "Role of Premises in Visual Question Answering." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78030.

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In this work, we make a simple but important observation questions about images often contain premises -- objects and relationships implied by the question -- and that reasoning about premises can help Visual Question Answering (VQA) models respond more intelligently to irrelevant or previously unseen questions. When presented with a question that is irrelevant to an image, state-of-the-art VQA models will still answer based purely on learned language biases, resulting in nonsensical or even misleading answers. We note that a visual question is irrelevant to an image if at least one of its pr

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10

Newman-Griffis, Denis R. "Capturing Domain Semantics with Representation Learning: Applications to Health and Function." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1587658607378958.

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11

Augustsson, Christopher. "Multipurpose Case-Based Reasoning System, Using Natural Language Processing." Thesis, Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-104890.

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Working as a field technician of any sort can many times be a challenging task. Often you find yourself alone, with a machine you have limited knowledge about, and the only support you have are the user manuals. As a result, it is not uncommon for companies to aid the technicians with a knowledge base that often revolves around some share point. But, unfortunately, the share points quickly get cluttered with too much information that leaves the user overwhelmed. Case-based reasoning (CBR), a form of problem-solving technology, uses previous cases to help users solve new problems they encounter

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12

Ibrahim, Hussain. "Detection of online radicalisation in the Maldivian language, Dhivehi." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2023. https://ro.ecu.edu.au/theses/2710.

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Early detection of online radical content is important for intelligence services to combat radicalisation and terrorism. This research was motivated by the lack of language tools in the detection of radicalisation in Dhivehi. The radical text data that is populated online in Dhivehi is increasing and taxing the capabilities of human open-source intelligence operatives. This research answered the question, “What methods are most suited for the detection of online radicalisation in the Maldivian language, Dhivehi?”. At the time of this research, there were no known language-based technologies or

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13

Bui, Anh Duc. "Visual Scene Understanding through Scene Graph Generation and Joint Learning." Thesis, University of Sydney, 2023. https://hdl.handle.net/2123/29954.

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Deep visual scene understanding is an essential part for the development of high-level visual understanding tasks such as storytelling or Visual Question Answering. One of the proposed solutions for such purposes were Scene Graphs, with the capacity to represent the semantic details of images into abstract elements using a graph structure which is both suitable for machine processing as well as human understanding. However, automatically generating reasonable and informative scene graphs remains a challenge due to the problem of long tail biases present in the annotated data available. Therefo

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14

Franceschelli, Giorgio. "Generative Deep Learning and Creativity." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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“Non ha la presunzione di originare nulla; può solo fare ciò che noi sappiamo ordinarle di fare”. Così, oltre 150 anni fa, Lady Lovelace commentava la Macchina Analitica di Babbage, l’antenato dei nostri computer. Una frase che, a distanza di tanti anni, suona quasi come una sfida: grazie alla diffusione delle tecniche di Generative Deep Learning e alle ricerche nell’ambito della Computational Creativity, sempre più sforzi sono stati destinati allo smentire l’ormai celebre Obiezione della Lovelace. Proprio a partire da questa, quattro domande formano i capisaldi della Computational Creativity:

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15

Rossi, Alex. "Self-supervised information retrieval: a novel approach based on Deep Metric Learning and Neural Language Models." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.

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Most of the existing open-source search engines, utilize keyword or tf-idf based techniques to find relevant documents and web pages relative to an input query. Although these methods, with the help of a page rank or knowledge graphs, proved to be effective in some cases, they often fail to retrieve relevant instances for more complicated queries that would require a semantic understanding to be exploited. In this Thesis, a self-supervised information retrieval system based on transformers is employed to build a semantic search engine over the library of Gruppo Maggioli company. Semantic sear

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16

Avenberg, Anna. "Automatic language identification of short texts." Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-421032.

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The world is growing more connected through the use of online communication, exposing software and humans to all the world's languages. While devices are able to understand and share the raw data between themselves and with humans, the information itself is not expressed in a monolithic format. This causes issues both in the human to computer interaction and human to human communication. Automatic language identification (LID) is a field within artificial intelligence and natural language processing that strives to solve a part of these issues by identifying languages from text, sign language

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Ray, Arijit. "The Art of Deep Connection - Towards Natural and Pragmatic Conversational Agent Interactions." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78335.

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As research in Artificial Intelligence (AI) advances, it is crucial to focus on having seamless communication between humans and machines in order to effectively accomplish tasks. Smooth human-machine communication requires the machine to be sensible and human-like while interacting with humans, while simultaneously being capable of extracting the maximum information it needs to accomplish the desired task. Since a lot of the tasks required to be solved by machines today involve the understanding of images, training machines to have human-like and effective image-grounded conversations with h

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18

Santiago, Dionny. "A Model-Based AI-Driven Test Generation System." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3878.

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Achieving high software quality today involves manual analysis, test planning, documentation of testing strategy and test cases, and development of automated test scripts to support regression testing. This thesis is motivated by the opportunity to bridge the gap between current test automation and true test automation by investigating learning-based solutions to software testing. We present an approach that combines a trainable web component classifier, a test case description language, and a trainable test generation and execution system that can learn to generate new test cases. Training da

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Avramidis, Eleftherios [Verfasser], and Hans [Akademischer Betreuer] Uszkoreit. "Comparative Quality Estimation for Machine Translation. An Application of Artificial Intelligence on Language Technology using Machine Learning of Human Preferences / Eleftherios Avramidis ; Betreuer: Hans Uszkoreit." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2019. http://d-nb.info/1181096073/34.

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20

Chaer, Iúri. "Um estudo sobre a Teoria da Predição aplicada à análise semântica de Linguagens Naturais." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/3/3141/tde-16112010-101029/.

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Neste trabalho, estuda-se o aprendizado computacional como um problema de indução. A partir de uma proposta de arquitetura de um sistema de análise semântica de Linguagens Naturais, foram desenvolvidos e testados individualmente os dois módulos necessários para a sua construção: um pré-processador capaz de mapear o conteúdo de textos para uma representação onde a semântica de cada símbolo fique explícita e um módulo indutor capaz de gerar teorias para explicar sequências de eventos. O componente responsável pela indução de teorias implementa uma versão restrita do Preditor de Solomonoff, capaz

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Sinclair, Andrew J. "PREDICTING MUSIC GENRE PREFERENCES BASED ON ONLINE COMMENTS." DigitalCommons@CalPoly, 2014. https://digitalcommons.calpoly.edu/theses/1268.

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Communication Accommodation Theory (CAT) states that individuals adapt to each other’s communicative behaviors. This adaptation is called “convergence.” In this work we explore the convergence of writing styles of users of the online music distribution plat- form SoundCloud.com. In order to evaluate our system we created a corpus of over 38,000 comments retrieved from SoundCloud in April 2014. The corpus represents comments from 8 distinct musical genres: Classical, Electronic, Hip Hop, Jazz, Country, Metal, Folk, and World. Our corpus contains: short comments, frequent misspellings, little se

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22

Del, Vecchio Matteo. "Improving Deep Question Answering: The ALBERT Model." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20414/.

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Natural Language Processing is a field of Artificial Intelligence referring to the ability of computers to understand human speech and language, often in a written form, mainly by using Machine Learning and Deep Learning methods to extract patterns. Languages are challenging by definition, because of their differences, their abstractions and their ambiguities; consequently, their processing is often very demanding, in terms of modelling the problem and resources. Retrieving all sentences in a given text is something that can be easily accomplished with just few lines of code, but what about c

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23

Loetzsch, Martin. "Lexicon formation in autonomous robots." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2015. http://dx.doi.org/10.18452/17121.

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"Die Bedeutung eines Wortes ist sein Gebrauch in der Sprache". Ludwig Wittgenstein führte diese Idee in der ersten Hälfte des 20. Jahrhunderts in die Philosophie ein und in verwandten Disziplinen wie der Psychologie und Linguistik setzte sich vor allem in den letzten Jahrzehnten die Ansicht durch, dass natürliche Sprache ein dynamisches System arbiträrer und kulturell gelernter Konventionen ist. Forscher um Luc Steels übertrugen diesen Sprachbegriff seit Ende der 90er Jahre auf das Gebiet der Künstlichen Intelligenz, indem sie zunächst Software-Agenten und später Robotern mittels sogen

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Bazzocchi, Luca. "User Internet Protection mediante Classificazione di Pagine Web con Text Mining." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/21640/.

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La classificazione di pagine web, ovvero il raggruppamento delle pagine in categorie sulla base del contenuto, come testo in linguaggio naturale, link, immagini e video sta diventando un problema sempre più importante da affrontare ed è proprio attraverso la conoscenza, ottenuta dai sorgenti html, che si cerca di raggiungere tale classificazione. Le pagine web e quindi i loro sorgenti html, non sono presenti né in schemi né in modelli composti da regole tali da definire la forma e tipologia dei dati contenuti, questo porta ad una loro difficile comprensione. Il Text Mining è il processo

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25

Magwele, Peter. "Teaching higher order thinking skills in the English first additional language learning classroom : a case of five intermediate classrooms in Mankweng Circuit." Thesis, University of Limpopo, 2019. http://hdl.handle.net/10386/2893.

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Thesis (M. A. (English Studies)) --University of Limpopo, 2019<br>There is a universal consensus among educationalists and cognitive development theorists that integration of higher order thinking (HOT) in language teaching has farreaching positive implications in learners‘ future. Their extensive body of research clearly indicates the interrelationship between language and thinking. It shows that to develop well-rounded learners who can later deal capably with varying demands of the 21st century, teaching them linguistic and cognitive skills concurrently is a prerequisite. However, there is s

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Kalitvianski, Ruslan. "Traitements formels et sémantiques des échanges et des documents textuels liés à des activités collaboratives." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAM012/document.

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Cette thèse s’inscrit dans la problématique de l’extraction de sens à partir de textes et flux textuels, produits dans notre cas lors de processus collaboratifs. Plus précisément, nous nous intéressons aux courriels de travail et aux documents textuels objets de collaboration, avec une première application aux documents éducatifs. La motivation de cet intérêt est d’aider les utilisateurs à accéder plus rapidement aux informations utiles ; nous cherchons donc à les repérer dans les textes. Ainsi, nous nous intéressons aux tâches dans les courriels, et aux fragments de documents éducatifs qui co

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27

Lilja, Adam, and Max Kihlborg. "Important criteria when choosing a conversational AI platform for enterprises." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-280896.

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This paper evaluates and analyzes three conversational AI-platforms; Dialogflow (Google), Watson Assistant (IBM) and Teneo (Artificial Solutions) on how they perform based on a set of criteria; pricing model, ease-of-use, efficiency, experience working in the software and what results to expect from each platform. The main focus was to investigate the platforms in order to acquire an understanding of which platform would best be suited for enterprises. The platforms were compared by performing a variety of tasks aiming to answer these questions. The technical research was combined with an anal

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Tabassum, Binte Jafar Jeniya. "Information Extraction From User Generated Noisy Texts." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1606315356821532.

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Rios, Anthony. "Deep Neural Networks for Multi-Label Text Classification: Application to Coding Electronic Medical Records." UKnowledge, 2018. https://uknowledge.uky.edu/cs_etds/71.

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Coding Electronic Medical Records (EMRs) with diagnosis and procedure codes is an essential task for billing, secondary data analyses, and monitoring health trends. Both speed and accuracy of coding are critical. While coding errors could lead to more patient-side financial burden and misinterpretation of a patient’s well-being, timely coding is also needed to avoid backlogs and additional costs for the healthcare facility. Therefore, it is necessary to develop automated diagnosis and procedure code recommendation methods that can be used by professional medical coders. The main difficulty wit

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Liu, Xiao. "Fast recursive biomedical event extraction." Thesis, Compiègne, 2014. http://www.theses.fr/2014COMP1963/document.

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L’internet et les nouvelles formes de média de communication, d’information, et de divertissement ont entraîné une croissance massive de la quantité des données numériques. Le traitement et l’interprétation automatique de ces données permettent de créer des bases de connaissances, de rendre les recherches plus efficaces et d’effectuer des recherches sur les médias sociaux. Les travaux de recherche sur le traitement automatique du langage naturel concernent la conception et le développement d’algorithmes, qui permettent aux ordinateurs de traiter automatiquement le langage naturel dans les text

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Sapena, Masip Emili. "A constraint-based hypergraph partitioning approach to coreference resolution." Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/83904.

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The objectives of this thesis are focused on research in machine learning for coreference resolution. Coreference resolution is a natural language processing task that consists of determining the expressions in a discourse that mention or refer to the same entity. The main contributions of this thesis are (i) a new approach to coreference resolution based on constraint satisfaction, using a hypergraph to represent the problem and solving it by relaxation labeling; and (ii) research towards improving coreference resolution performance using world knowledge extracted from Wikipedia. The

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Bevans, Brandon. "Categorizing Blog Spam." DigitalCommons@CalPoly, 2016. https://digitalcommons.calpoly.edu/theses/1623.

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The internet has matured into the focal point of our era. Its ecosystem is vast, complex, and in many regards unaccounted for. One of the most prevalent aspects of the internet is spam. Similar to the rest of the internet, spam has evolved from simply meaning ‘unwanted emails’ to a blanket term that encompasses any unsolicited or illegitimate content that appears in the wide range of media that exists on the internet. Many forms of spam permeate the internet, and spam architects continue to develop tools and methods to avoid detection. On the other side, cyber security engineers continue to de

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Bang, Sanghun. "Development framework for language acquisition based on the embodied cognition : case of problem solving and gesture." Electronic Thesis or Diss., Paris 8, 2021. http://www.theses.fr/2021PA080007.

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L'idée de “cognition incarnée” part du constat que notre cerveau est un organe vivant relié à un corps (lui aussi vivant) plongé dans un environnement sur lequel il s'agit. Cette inscription corporelle, vivante et active du cerveau a une incidence majeure sur la pensée (pris dans le sens large de “cognition”). Cela signifie que les représentations ont une composante corporelle issue de notre système sensori-moteur, mais aussi émotionnel lors de la réalisation de nos actions sensorimotrices et de nos actions planifiées. Il est alors possible de concevoir le langage comme essentiellement métapho

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Sancho, Escrivá José Vicente. "Utilidad de las nuevas tecnologías en la mejora de la comunicación médico-paciente en el área de salud mental: aportaciones de la inteligencia artificial y el procesamiento del lenguaje natural." Doctoral thesis, Universitat Jaume I, 2021. http://dx.doi.org/10.6035/14111.2021.301397.

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La sociedad de la información ha evolucionado vertiginosamente con las nuevas tecnologías. La inteligencia artificial se ha convertido en la referencia de esta evolución. En este campo, el procesamiento de lenguaje natural alcanza gran aceptación en disciplinas que trabajen el Big Data. Queremos ver qué aporta y analizamos el uso de las nuevas tecnologías en la enfermedad mental, el uso de las apps en estos pacientes y su impacto en la comunicación médico-paciente. Pretendemos ver si las técnicas de procesamiento del lenguaje natural aportan mejoras en el análisis de los datos obtenidos con té

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Sazonau, Viachaslau. "General terminology induction in description logics." Thesis, University of Manchester, 2017. https://www.research.manchester.ac.uk/portal/en/theses/general-terminology-induction-in-description-logics(63142865-d610-4041-84fa-764af1759554).html.

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In computer science, an ontology is a machine-processable representation of knowledge about some domain. Ontologies are encoded in ontology languages, such as the Web Ontology Language (OWL) based on Description Logics (DLs). An ontology is a set of logical statements, called axioms. Some axioms make universal statements, e.g. all fathers are men, while others record data, i.e. facts about specific individuals, e.g. Bob is a father. A set of universal statements is called TBox, as it encodes terminology, i.e. schema-level conceptual relationships, and a set of facts is called ABox, as it encod

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Khan, Sifat Shahriar. "Power Outage Management using Social Sensing." University of Akron / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1556833736835808.

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Roos, Sofie. "Chatbots in education : A passing trend or a valuable pedagogical tool?" Thesis, Uppsala universitet, Institutionen för informatik och media, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-355054.

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Digitalizing education and reinventing the learning experience is one of the big challenges in this age of information. In the eld of E-learning, the application of a chatbot as part of the education has shown interesting potential, both as a teaching and administrative tool. Chatbots have been 'trending' for a few years and quite a few papers examining it in the educational sector has been published, albeit very little interest seems to have been given to the summation of this knowledge. In an attempt to fill the knowledge gap this thesis performed a literature study to examine the documented

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Dhyani, Dushyanta Dhyani. "Boosting Supervised Neural Relation Extraction with Distant Supervision." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524095334803486.

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Zarei, Koosha. "Fake identity & fake activity detection in online social networks based on transfer learning." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS008.

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Les médias sociaux ont permis de connecter un plus grand nombre de personnes dans le monde entier et d'accroître la facilité d'accès à des contenus gratuits, mais ils sont confrontés à des phénomènes critiques tels que les faux contenus, les fausses identités et les fausses activités. La détection de faux contenus sur les médias sociaux est récemment devenue une recherche émergente qui attire une attention considérable. une recherche émergente qui suscite une attention considérable. Dans ce domaine, les fausses identités jouent un rôle important dans la production et la propagation de faux con

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Shang, Guokan. "Spoken Language Understanding for Abstractive Meeting Summarization Unsupervised Abstractive Meeting Summarization with Multi-Sentence Compression and Budgeted Submodular Maximization. Energy-based Self-attentive Learning of Abstractive Communities for Spoken Language Understanding Speaker-change Aware CRF for Dialogue Act Classification." Thesis, Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAX011.

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Grâce aux progrès impressionnants qui ont été réalisés dans la transcription du langage parlé, il est de plus en plus possible d'exploiter les données transcrites pour des tâches qui requièrent la compréhension de ce que l'on dit dans une conversation. Le travail présenté dans cette thèse, réalisé dans le cadre d'un projet consacré au développement d'un assistant de réunion, contribue aux efforts en cours pour apprendre aux machines à comprendre les dialogues des réunions multipartites. Nous nous sommes concentrés sur le défi de générer automatiquement les résumés abstractifs de réunion.Nous p

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Silvestre, Cerdà Joan Albert. "Different Contributions to Cost-Effective Transcription and Translation of Video Lectures." Doctoral thesis, Universitat Politècnica de València, 2016. http://hdl.handle.net/10251/62194.

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[EN] In recent years, on-line multimedia repositories have experiencied a strong growth that have made them consolidated as essential knowledge assets, especially in the area of education, where large repositories of video lectures have been built in order to complement or even replace traditional teaching methods. However, most of these video lectures are neither transcribed nor translated due to a lack of cost-effective solutions to do so in a way that gives accurate enough results. Solutions of this kind are clearly necessary in order to make these lectures accessible to speakers of differ

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Pàmies, Massip Marc. "Multilingual identification of offensive content in social media." Thesis, Linköpings universitet, Artificiell intelligens och integrerade datorsystem, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167381.

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In today’s society there is a large number of social media users that are free to express their opinion on shared platforms. The socio-cultural differences between the people behind those accounts (in terms of ethnicity, gender, sexual orientation, religion, politics, . . . ) give rise to an important percentage of online discussions that make use of offensive language, which often affects in a negative way the psychological well-being of the victims. In order to address the problem, the endless stream of user-generated content engenders a need to find an accurate and scalable solution to dete

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Cozzi, Riccardo. "Using semantic entities to improve the distillation of transformers." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2022.

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In the last decade, the size of deep neural architectures implied in Natural Language Processing (NLP) has increased exponentially, reaching in some cases with hundreds of billions of parameters. Although, training and deploying these huge architectures is an extremely resource-demanding process and the costs are often not affordable in real-world applications. For these reasons, lots of research and industrial efforts are investigating solutions to reduce the size of these models but at the same time maintain high performance. This work was about studying and experimenting Knowledge Disti

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Li, Jie. "Intention-driven textual semantic analysis." School of Computer Science and Software Engineering, 2008. http://ro.uow.edu.au/theses/104.

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The explosion of World Wide Web has brought endless amount of information within our reach. In order to take advantage of this phenomenon, text search becomes a major contemporary research challenge. Due to the nature of the Web, assisting users to find desired information is still a challenging task. In this thesis, we investigate semantic anlaysis techniques which can facilitate the search process at semantic level. We also study the problem that short queries are less informative and difficult to convey the user's intention into the search service system. We propose a generalized frame

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Bartl, Eduard. "Mathematical foundations of graded knowledge spaces." Diss., Online access via UMI:, 2009.

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Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Systems Science and Industrial Engineering, 2009.<br>Includes bibliographical references.

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Augusitne, Eriq A. "SPOONS: NETFLIX OUTAGE DETECTION USING MICROTEXT CLASSIFICATION." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/945.

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Every week there are over a billion new posts to Twitter services and many of those messages contain feedback to companies about their services. One company that recognizes this unused source of information is Netflix. That is why Netflix initiated the development of a system that lets them respond to the millions of Twitter and Netflix users that are acting as sensors and reporting all types of user visible outages. This system enhances the feedback loop between Netflix and its customers by increasing the amount of customer feedback that Netflix receives and reducing the time it takes for Net

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Mancini, Eleonora. "Disruptive Situations Detection on Public Transports through Speech Emotion Recognition." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/24721/.

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In this thesis, we describe a study on the application of Machine Learning and Deep Learning methods for Voice Activity Detection (VAD) and Speech Emotion Recognition (SER). The study is in the context of a European project whose objective is to detect disruptive situations in public transports. To this end, we developed an architecture, implemented a prototype and ran validation tests on a variety of options. The architecture consists of several modules. The denoising module was realized through the use of a filter and the VAD module through an open-source toolkit, while the SER system was

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Khatri, Chandra P. "Real-time road traffic information detection through social media." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53889.

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In current study, a mechanism to extract traffic related information such as congestion and incidents from textual data from the internet is proposed. The current source of data is Twitter, however, the same mechanism can be extended to any kind of text available on the internet. As the data being considered is extremely large in size automated models are developed to stream, download, and mine the data in real-time. Furthermore, if any tweet has traffic related information then the models should be able to infer and extract this data. To pursue this task, Artificial Intelligence, Machine Lear

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Terreau, Enzo. "Apprentissage de représentations d'auteurs et d'autrices à partir de modèles de langue pour l'analyse des dynamiques d'écriture." Electronic Thesis or Diss., Lyon 2, 2024. http://www.theses.fr/2024LYO20001.

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La démocratisation récente et massive des outils numériques a donné à tous le moyen de produire de l'information et de la partager sur le web, que ce soit à travers des blogs, des réseaux sociaux, des plateformes de partage, ... La croissance exponentielle de cette masse d'information disponible, en grande partie textuelle, nécessite le développement de modèles de traitement automatique du langage naturel (TAL), afin de la représenter mathématiquement pour ensuite la classer, la trier ou la recommander. C'est l'apprentissage de représentation. Il vise à construire un espace de faible dimension

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Cripwell, Liam. "Controllable and Document-Level Text Simplification." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0186.

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La simplification de texte est une tâche qui consiste à réécrire un texte pour le rendre plus facile à lire et à comprendre pour un public plus large, tout en exprimant toujours le même sens fondamental. Cela présente des avantages potentiels pour certains utilisateurs (par exemple, les locuteurs non natifs, les enfants, les personnes ayant des difficultés de lecture), tout en étant prometteur en tant qu'étape de prétraitement pour les tâches de Traitement Automatique des Langues (TAL) en aval. Les progrès récents dans les modèles génératifs neuronaux ont conduit au développement de systèmes c

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