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1

Філоненко, О. В., Олена Петрівна Черних та Олександр Миколайович Шеін. "Фільтрування інтернет спаму за допомогою обробки природної мови". Thesis, Національний технічний університет "Харківський політехнічний інститут", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/43684.

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2

Scheible, Silke. "Computational treatment of superlatives." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4153.

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The use of gradable adjectives and adverbs represents an important means of expressing comparison in English. The grammatical forms of comparatives and superlatives are used to express explicit orderings between objects with respect to the degree to which they possess some gradable property. While comparatives are commonly used to compare two entities (e.g., “The blue whale is larger than an African elephant”), superlatives such as “The blue whale is the largest mammal” are used to express a comparison between a target entity (here, the blue whale) and its comparison set (the set of mammals),
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Hachey, Benjamin. "Towards generic relation extraction." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3978.

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A vast amount of usable electronic data is in the form of unstructured text. The relation extraction task aims to identify useful information in text (e.g., PersonW works for OrganisationX, GeneY encodes ProteinZ) and recode it in a format such as a relational database that can be more effectively used for querying and automated reasoning. However, adapting conventional relation extraction systems to new domains or tasks requires significant effort from annotators and developers. Furthermore, previous adaptation approaches based on bootstrapping start from example instances of the target relat
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NUNES, THIAGO RIBEIRO. "BUILDING RELATION EXTRACTORS THROUGH DISTANT SUPERVISION." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2012. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=21588@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Um problema conhecido no processo de construção de extratores de relações semânticas supervisionados em textos em linguagem natural é a disponibilidade de uma quantidade suficiente de exemplos positivos para um conjunto amplo de relações-alvo. Este trabalho apresenta uma abordagem supervisionada a distância para construção de extratores de relações a um baixo custo combinando duas das maiores fontes de informação estruturada e não estruturada disponíveis na Web, o DBpedia e a
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Minard, Anne-Lyse. "Extraction de relations en domaine de spécialité." Phd thesis, Université Paris Sud - Paris XI, 2012. http://tel.archives-ouvertes.fr/tel-00777749.

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La quantité d'information disponible dans le domaine biomédical ne cesse d'augmenter. Pour que cette information soit facilement utilisable par les experts d'un domaine, il est nécessaire de l'extraire et de la structurer. Pour avoir des données structurées, il convient de détecter les relations existantes entre les entités dans les textes. Nos recherches se sont focalisées sur la question de l'extraction de relations complexes représentant des résultats expérimentaux, et sur la détection et la catégorisation de relations binaires entre des entités biomédicales. Nous nous sommes intéressée aux
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Augenstein, Isabelle. "Web relation extraction with distant supervision." Thesis, University of Sheffield, 2016. http://etheses.whiterose.ac.uk/13247/.

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Being able to find relevant information about prominent entities quickly is the main reason to use a search engine. However, with large quantities of information on the World Wide Web, real time search over billions of Web pages can waste resources and the end user’s time. One of the solutions to this is to store the answer to frequently asked general knowledge queries, such as the albums released by a musical artist, in a more accessible format, a knowledge base. Knowledge bases can be created and maintained automatically by using information extraction methods, particularly methods to extrac
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Simon, Etienne. "Deep Learning for Unsupervised Relation Extraction." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS198.

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Détecter les relations exprimées dans un texte est un problème fondamental de la compréhension du langage naturel. Il constitue un pont entre deux approches historiquement distinctes de l'intelligence artificielle, celles à base de représentations symboliques et distribuées. Cependant, aborder ce problème sans supervision humaine pose plusieurs problèmes et les modèles non supervisés ont des difficultés à faire écho aux avancées des modèles supervisés. Cette thèse aborde deux lacunes des approches non supervisées : le problème de la régularisation des modèles discriminatifs et le problème d'ex
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Yeh, Hui-Syuan. "Prompt-based Relation Extraction for Pharmacovigilance." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASG097.

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L'extraction de connaissances à jour à partir de sources textuelles diverses est importante pour la santé publique. Alors que les sources professionnelles, notamment les revues scientifiques et les notes cliniques, fournissent les connaissances les plus fiables, les observations apportées dans les forums de patients et les médias sociaux permettent d'obtenir des informations complémentaires pour certains thèmes. Détecter les entités et leurs relations dans ces sources variées est particulièrement précieux. Nous nous concentrons sur l'extraction de relations dans le domaine médical. Nous commen
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Jean-Louis, Ludovic. "Approches supervisées et faiblement supervisées pour l’extraction d’événements et le peuplement de bases de connaissances." Thesis, Paris 11, 2011. http://www.theses.fr/2011PA112288/document.

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La plus grande partie des informations disponibles librement sur le Web se présentent sous une forme textuelle, c'est-à-dire non-structurée. Dans un contexte comme celui de la veille, il est très utile de pouvoir présenter les informations présentes dans les textes sous une forme structurée en se focalisant sur celles jugées pertinentes vis-à-vis du domaine d'intérêt considéré. Néanmoins, lorsque l'on souhaite traiter ces informations de façon systématique, les méthodes manuelles ne sont pas envisageables du fait du volume important des données à considérer.L'extraction d'information s'inscrit
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Afzal, Naveed. "Unsupervised relation extraction for e-learning applications." Thesis, University of Wolverhampton, 2011. http://hdl.handle.net/2436/299064.

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In this modern era many educational institutes and business organisations are adopting the e-Learning approach as it provides an effective method for educating and testing their students and staff. The continuous development in the area of information technology and increasing use of the internet has resulted in a huge global market and rapid growth for e-Learning. Multiple Choice Tests (MCTs) are a popular form of assessment and are quite frequently used by many e-Learning applications as they are well adapted to assessing factual, conceptual and procedural information. In this thesis, we pre
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Imani, Mahsa. "Evaluating open relation extraction over conversational texts." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/45978.

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In this thesis, for the first time the performance of Open IE systems on conversational data has been studied. Due to lack of test datasets in this domain, a method for creating the test dataset covering a wide range of conversational data has been proposed. Conversational text is more complex and challenging for relation extraction because of its cryptic content and ungrammatical colloquial language. As a consequence text simplification has been used as a remedy to empower Open IE tools for relation extraction. Experimental results show that text simplification helps OLLIE, a state of the art
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Loper, Edward (Edward Daniel) 1977. "Applying semantic relation extraction to information retrieval." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/86521.

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Bai, Fan. "Structured Minimally Supervised Learning for Neural Relation Extraction." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu159666392917093.

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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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Taillé, Bruno. "Contextualization and Generalization in Entity and Relation Extraction." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS266.

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Depuis 2018, le transfert de modèles de langue pré-entraînés et la préservation de leurs capacités de contextualisation ont permis d'atteindre des performances sans précédent sur les benchmarks de Traitement Automatique des Langues. Cependant, alors que ces modèles atteignent des scores impressionnants, leurs capacités de compréhension apparaissent assez peu développées, révélant les limites des jeux de données de référence pour identifier leurs facteurs de performance et pour mesurer précisément leur capacité de compréhension. Dans cette thèse, nous étudions la généralisation à des faits inco
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Zhang, Shaomin. "Thematic knowledge extraction." Thesis, Nottingham Trent University, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.272437.

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Saberi, Elham <1989&gt. "Extraction of semantic relations in Persian text." Master's Degree Thesis, Università Ca' Foscari Venezia, 2017. http://hdl.handle.net/10579/10481.

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The purpose of this thesis is introduce a way to make a reliable structure for Persian text in the web by finding semantic relations between Persian words. There is a corpus for Persian text with label for each word (label such as : Noun or Adjective) , There is a bunch of patterns to extraction the relations , system make a comparison and give the relations as a result.(relations such as this words are Ezafe takhsisi or they are Ezafe jensi )
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Dahlbom, Norgren Nils. "Relation Classification Between the Extracted Entities of Swedish Verdicts." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-206829.

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This master thesis investigated how well a multiclass support vector machine approach is at classifying a fixed number of interpersonal relations between extracted entities of people from Swedish verdicts. With the help of manually tagged extracted pairs of people entities called relations, a multiclass support vector machine was used to train and test the performance of the classification. Different features and parameters were tested to optimize the method, and for the final experiment, a micro precision and recall of 91.75% were found. For macro precision and recall, the result was 73.29% a
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Granada, Roger Leitzke. "Evaluation of methods for taxonomic relation extraction from text." Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2015. http://tede2.pucrs.br/tede2/handle/tede/7108.

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Submitted by Setor de Tratamento da Informa??o - BC/PUCRS (tede2@pucrs.br) on 2016-12-26T16:34:57Z No. of bitstreams: 1 TES_ROGER_LEITZKE_GRANADA_COMPLETO.pdf: 2483840 bytes, checksum: 8f81d3f0496d8fa8d3a1b013dfdf932b (MD5)<br>Made available in DSpace on 2016-12-26T16:34:57Z (GMT). No. of bitstreams: 1 TES_ROGER_LEITZKE_GRANADA_COMPLETO.pdf: 2483840 bytes, checksum: 8f81d3f0496d8fa8d3a1b013dfdf932b (MD5) Previous issue date: 2015-09-28<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior - CAPES<br>Sistemas de informa??o modernos t?m mudado a ideia ?processamento de dados? para a i
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Chauhan, Geeticka. "REflex: Flexible framework for Relation Extraction in multiple domains." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122694.

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This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2019<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 81-89).<br>Relation Extraction (RE) refers to the problem of extracting semantic relationships between concepts in a given sentence, and is an important component of Natural Language Understanding (NLU). It has been popularly stu
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Wang, Wei. "Unsupervised Information Extraction From Text - Extraction and Clustering of Relations between Entities." Phd thesis, Université Paris Sud - Paris XI, 2013. http://tel.archives-ouvertes.fr/tel-00998390.

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Unsupervised information extraction in open domain gains more and more importance recently by loosening the constraints on the strict definition of the extracted information and allowing to design more open information extraction systems. In this new domain of unsupervised information extraction, this thesis focuses on the tasks of extraction and clustering of relations between entities at a large scale. The objective of relation extraction is to discover unknown relations from texts. A relation prototype is first defined, with which candidates of relation instances are initially extracted wit
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Savelev, Sergey U. "Extracts of salvia species : relation to potential cognitive therapy." Thesis, University of Newcastle Upon Tyne, 2003. http://hdl.handle.net/10443/608.

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BACKGROUND: Dementia is a neurodegenerative disease of the brain associated with cognitive and memory impairments. Despite recognition of several types of dementia, the Alzheimer type is the most studied and understood. The cholinergic theory of Alzheimer's disease led to the development of licensed drugs based on the inhibition of the enzyme acetylcholinesterase. Extracts of Salvia (sage) species have been reported to have cholinergic activities relevant to the treatment of Alzheimer's disease. AIMS: Lack of information on a chemical fingerprint of the extracts responsible for inhibition of t
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Conrath, Juliette. "Unsupervised extraction of semantic relations using discourse information." Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30202/document.

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La compréhension du langage naturel repose souvent sur des raisonnements de sens commun, pour lesquels la connaissance de relations sémantiques, en particulier entre prédicats verbaux, peut être nécessaire. Cette thèse porte sur la problématique de l'utilisation d'une méthode distributionnelle pour extraire automatiquement les informations sémantiques nécessaires à ces inférences de sens commun. Des associations typiques entre des paires de prédicats et un ensemble de relations sémantiques (causales, temporelles, de similarité, d'opposition, partie/tout) sont extraites de grands corpus, par l'
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Al, Qady Mohammed Abdelrahman. "Concept relation extraction using natural language processing the CRISP technique /." [Ames, Iowa : Iowa State University], 2008.

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Xavier, Clarissa Castell? "Learning non-verbal relations under open information extraction paradigm." Pontif?cia Universidade Cat?lica do Rio Grande do Sul, 2014. http://tede2.pucrs.br/tede2/handle/tede/5275.

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Made available in DSpace on 2015-04-14T14:50:19Z (GMT). No. of bitstreams: 1 466321.pdf: 1994049 bytes, checksum: fbbeef81814a876679c25f4e015925f5 (MD5) Previous issue date: 2014-03-12<br>O paradigma Open Information Extraction - Open IE (Extra??o Aberta de Informa??es) de extra??o de rela??es trabalha com a identifica??o de rela??es n?o definidas previamente, buscando superar as limita??es impostas pelos m?todos tradicionais de Extra??o de Informa??es como a depend?ncia de dom?nio e a dif?cil escalabilidade. Visando estender o paradigma Open IE para que sejam extra?das rela??es n?o expres
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Xavier, Clarissa Castellã. "Learning non-verbal relations under open information extraction paradigm." Pontifícia Universidade Católica do Rio Grande do Sul, 2014. http://hdl.handle.net/10923/7073.

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Made available in DSpace on 2015-03-17T02:01:01Z (GMT). No. of bitstreams: 1 000466321-Texto+Completo-0.pdf: 1994049 bytes, checksum: fbbeef81814a876679c25f4e015925f5 (MD5) Previous issue date: 2014<br>The Open Information Extraction (Open IE) is a relation extraction paradigm in which the target relationships cannot be specified in advance, and it aims to overcome the limitations imposed by traditional IE methods, such as domain-dependence and scalability. In order to extend Open IE to extract relationships that are not expressed by verbs from texts in English, we introduce CompIE, a compon
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ASSIS, PEDRO HENRIQUE RIBEIRO DE. "DISTANT SUPERVISION FOR RELATION EXTRACTION USING ONTOLOGY CLASS HIERARCHY-BASED FEATURES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2014. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=24296@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>Extração de relacionamentos é uma etapa chave para o problema de identificação de uma estrutura em um texto em formato de linguagem natural. Em geral, estruturas são compostas por entidades e relacionamentos entre elas. As propostas de solução com maior sucesso aplicam aprendizado de máquina supervisionado a corpus anotados à mão para a criação de classificadores de alta precisão. Embora alcancem boa robustez, corpus criados à mão não são esc
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Nguyen, Truc-Vien T. "End-to-End Relation Extraction via Syntactic Structures and Semantic Resources." Doctoral thesis, Università degli studi di Trento, 2011. https://hdl.handle.net/11572/369167.

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Information Extraction (IE) aims at mapping texts into fixed structure representing the key information. A typical IE system will try to answer the questions like who are present in the text, what events happen and when these events happen. The task is making possible significant advances in applications that require deep understanding capabilities such as question-answering engines, dialogue systems, or the semantic web. Due to the huge effort and time consumation of developping extraction systems by domain experts, our approach focuses on machine learning methods that can accurately infer an
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Nguyen, Truc-Vien T. "End-to-End Relation Extraction via Syntactic Structures and Semantic Resources." Doctoral thesis, University of Trento, 2011. http://eprints-phd.biblio.unitn.it/594/1/TVNguyen_Dissertation_old.pdf.

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Information Extraction (IE) aims at mapping texts into fixed structure representing the key information. A typical IE system will try to answer the questions like who are present in the text, what events happen and when these events happen. The task is making possible significant advances in applications that require deep understanding capabilities such as question-answering engines, dialogue systems, or the semantic web. Due to the huge effort and time consumation of developping extraction systems by domain experts, our approach focuses on machine learning methods that can accurately infer a
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Tang, Anfu. "Leveraging linguistic and semantic information for relation extraction from domain-specific texts." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG081.

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Cette thèse a pour objet l'extraction d'informations relationnelles à partir de documents scientifiques biomédicaux, c'est-à-dire la transformation de texte non structuré en information structurée exploitable par une machine. En tant que tâche dans le domaine du traitement automatique des langues (TAL), l'extraction de relations sémantiques spécialisées entre entités textuelles rend explicite et formalise les structures sous-jacentes. Les méthodes actuelles à l'état de l'art s'appuient sur de l'apprentissage supervisé, plus spécifiquement l'ajustement de modèles de langue pré-entraînés comme B
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Achouri, Abdelghani. "Extraction de relations d'associations maximales dans les textes : représentation graphique." Thèse, Université du Québec à Trois-Rivières, 2012. http://depot-e.uqtr.ca/6132/1/030374207.pdf.

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Califf, Mary Elaine. "Relational learning techniques for natural language information extraction /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Lord, Dale. "Relational Database for Visual Data Management." International Foundation for Telemetering, 2005. http://hdl.handle.net/10150/604893.

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ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada<br>Often it is necessary to retrieve segments of video with certain characteristics, or features, from a large archive of footage. This paper discusses how image processing algorithms can be used to automatically create a relational database, which indexes the video archive. This feature extraction can be performed either upon acquisition or in post processing. The database can then be queried to
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Karoui, Lobna. "Extraction contextuelle d'ontologie par fouille de données." Paris 11, 2008. http://www.theses.fr/2008PA112220.

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L’objectif de cette thèse est d’automatiser au maximum le processus de construction d’une ontologie à partir de pages web, en étudiant notamment l’impact que peut avoir la fouille de données dans une telle tâche. Pour construire l’ontologie, nous avons exploité la structure HTML du document étudié afin de pouvoir bien définir le contexte à mettre en œuvre. Ce dernier est structuré sous la forme d’une hiérarchie de contextes. Puis, nous avons défini un algorithme de clustering hiérarchique dédié à l’extraction de concepts ontologiques intitulé ‘ECO’ ; il est basé sur l’algorithme Kmeans et guid
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Marshman, Elizabeth. "The cause relation in biopharmaceutical corpora: English and French patterns for knowledge extraction." Thesis, University of Ottawa (Canada), 2002. http://hdl.handle.net/10393/6385.

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One of the most important aspects of a terminologist's work is extracting conceptual information about terms from texts. Because this task is so time-consuming, researchers are trying to develop tools which will extract conceptual information semi-automatically. Many of these tools are based on the use of linguistic indicators called knowledge patterns. This thesis aims to identify some knowledge patterns in English and French which indicate the conceptual relation of cause and effect. This relation, though not as widely studied as those of generic to specific or part to whole, is critical
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Ryan, Russell J. (Russell John Wyatt). "Groundtruth budgeting : a novel approach to semi-supervised relation extraction in medical language." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66456.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 67-69).<br>We address the problem of weakly-supervised relation extraction in hospital discharge summaries. Sentences with pre-identified concept types (for example: medication, test, problem, symptom) are labeled with the relationship between the concepts. We present a novel technique for weakly-supervised bootstrapping of a classifier for this task: Groundtruth Budgeting. In the case of highly-
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Xavier, Clarissa [Verfasser]. "Learning Non-Verbal Relations Under Open Information Extraction Paradigm / Clarissa Xavier." Munich : GRIN Verlag, 2015. http://d-nb.info/1097578720/34.

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Bourgeois, Thomas C. "English Relative Clause Extraction: A Syntactic and Semantic Approach." University of Arizona Linguistics Circle, 1989. http://hdl.handle.net/10150/226574.

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Within this paper we analyze the formation of and extraction from a specific type of noun phrase, namely that consisting of the definite article followed by a common noun modified by a relative clause, where the common noun can be the subject or the object of the modifying clause. Representative examples of this construction appear in Figure 1: (1) ( i ) . Sal knows the man Sid likes. (ii) . Sal knows the man who bought the carrot. The framework we assume here makes use of a system of functional syntactical and (corresponding) semantical types assigned to each item in the string. These types a
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Vempala, Alakananda. "Extracting Temporally-Anchored Spatial Knowledge." Thesis, University of North Texas, 2019. https://digital.library.unt.edu/ark:/67531/metadc1505146/.

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In my dissertation, I elaborate on the work that I have done to extract temporally-anchored spatial knowledge from text, including both intra- and inter-sentential knowledge. I also detail multiple approaches to infer spatial timeline of a person from biographies and social media. I present and analyze two strategies to annotate information regarding whether a given entity is or is not located at some location, and for how long with respect to an event. Specifically, I leverage semantic roles or syntactic dependencies to generate potential spatial knowledge and then crowdsource annotations to
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Morsi, Youcef Ihab. "Analyse linguistique et extraction automatique de relations sémantiques des textes en arabe." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCC019.

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Cette recherche porte sur le développement d’un outil de traitement automatique de la langue arabe standard moderne, au niveau morphologique et sémantique, avec comme objectif final l’extraction d’information dans le domaine de l’innovation technologique en entreprise. En ce qui concerne l’analyse morphologique, notre outil comprend plusieurs traitements successifs qui permettent d’étiqueter et de désambiguïser les occurrences dans les textes : une couche morphologique (Gibran 1.0), qui s’appuie sur les schèmes arabes comme traits distinctifs ; une couche contextuelle (Gibran 2.0), qui fait ap
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Darud, Véronique. "Relations synthèse-structure-propriétés de polyuréthannes linéaires susceptibles d’être utilises comme liant de particules magnétiques." Lyon, INSA, 1988. http://www.theses.fr/1988ISAL0073.

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Cette étude vise à mettre au point un liant polyuréthanne thermoplastique, de type polyéther, utilisé à la fabrication de bande magnétique. Son rôle est de permettre le couchage des particules sur un support polymère par voie solvant et d'assurer à l ' ensemble, cohésion et résistance à l'abrasion. L’utilisation simultanée, de deux sortes d’allongeurs de chaîne, en proportion variable, le di-β. β’ -hydroxyéthylétherhydroquinone (HQEE) et le néopentylglycol (NPG), a permis de réaliser divers compromis « structure – propriétés », susceptibles de contribuer à résoudre les problèmes posés par l'ut
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42

Ruiz, Fabo Pablo. "Concept-based and relation-based corpus navigation : applications of natural language processing in digital humanities." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEE053/document.

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La recherche en Sciences humaines et sociales repose souvent sur de grandes masses de données textuelles, qu'il serait impossible de lire en détail. Le Traitement automatique des langues (TAL) peut identifier des concepts et des acteurs importants mentionnés dans un corpus, ainsi que les relations entre eux. Ces informations peuvent fournir un aperçu du corpus qui peut être utile pour les experts d'un domaine et les aider à identifier les zones du corpus pertinentes pour leurs questions de recherche. Pour annoter automatiquement des corpus d'intérêt en Humanités numériques, les technologies TA
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43

Ratkovic, Zorana. "Predicative Analysis for Information Extraction : application to the biology domain." Thesis, Paris 3, 2014. http://www.theses.fr/2014PA030110.

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L’abondance de textes dans le domaine biomédical nécessite le recours à des méthodes de traitement automatique pour améliorer la recherche d’informations précises. L’extraction d’information (EI) vise précisément à extraire de l’information pertinente à partir de données non-structurées. Une grande partie des méthodes dans ce domaine se concentre sur les approches d’apprentissage automatique, en ayant recours à des traitements linguistiques profonds. L’analyse syntaxique joue notamment un rôle important, en fournissant une analyse précise des relations entre les éléments de la phrase.Cette thè
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44

Gonzàlez, Pellicer Edgar. "Unsupervised learning of relation detection patterns." Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/83906.

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L'extracció d'informació és l'àrea del processament de llenguatge natural l'objectiu de la qual és l'obtenir dades estructurades a partir de la informació rellevant continguda en fragments textuals. L'extracció d'informació requereix una quantitat considerable de coneixement lingüístic. La especificitat d'aquest coneixement suposa un inconvenient de cara a la portabilitat dels sistemes, ja que un canvi d'idioma, domini o estil té un cost en termes d'esforç humà. Durant dècades, s'han aplicat tècniques d'aprenentatge automàtic per tal de superar aquest coll d'ampolla de portabilitat, redui
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45

Tomczak, Jakub. "Algorithms for knowledge discovery using relation identification methods." Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2563.

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In this work a coherent survey of problems connected with relational knowledge representation and methods for achieving relational knowledge representation were presented. Proposed approach was shown on three applications: economic case, biomedical case and benchmark dataset. All crucial definitions were formulated and three main methods for relation identification problem were shown. Moreover, for specific relational models and observations’ types different identification methods were presented.<br>Double Diploma Programme, polish supervisor: prof. Jerzy Świątek, Wrocław University of Technol
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46

Chu, Timothy Sui-Tim. "Genealogy Extraction and Tree Generation from Free Form Text." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1796.

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Genealogical records play a crucial role in helping people to discover their lineage and to understand where they come from. They provide a way for people to celebrate their heritage and to possibly reconnect with family they had never considered. However, genealogical records are hard to come by for ordinary people since their information is not always well established in known databases. There often is free form text that describes a person’s life, but this must be manually read in order to extract the relevant genealogical information. In addition, multiple texts may have to be read in orde
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47

Wang, Jingcheng. "A Rule-based Methodology and Feature-based Methodology for Effect Relation Extraction in Chinese Unstructured Text." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/14152.

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The Chinese language differs significantly from English, both in lexical representation and grammatical structure. These differences lead to problems in the Chinese NLP, such as word segmentation and flexible syntactic structure. Many conventional methods and approaches in Natural Language Processing (NLP) based on English text are shown to be ineffective when attending to these language specific problems in late-started Chinese NLP. Relation Extraction is an area under NLP, looking to identify semantic relationships between entities in the text. The term “Effect Relation” is introduced in th
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48

Hakenberg, Jörg. "Mining relations from the biomedical literature." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2010. http://dx.doi.org/10.18452/16073.

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Textmining beschäftigt sich mit der automatisierten Annotierung von Texten und der Extraktion einzelner Informationen aus Texten, die dann für die Weiterverarbeitung zur Verfügung stehen. Texte können dabei kurze Zusammenfassungen oder komplette Artikel sein, zum Beispiel Webseiten und wissenschaftliche Artikel, umfassen aber auch textuelle Einträge in sonst strukturierten Datenbanken. Diese Dissertationsschrift bespricht zwei wesentliche Themen des biomedizinischen Textmining: die Extraktion von Zusammenhängen zwischen biologischen Entitäten ---das Hauptaugenmerk liegt dabei auf der Erkennung
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49

Alatrista-Salas, Hugo. "Extraction de relations spatio-temporelles à partir des données environnementales et de la santé." Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2013. http://tel.archives-ouvertes.fr/tel-00997539.

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Face à l'explosion des nouvelles technologies (mobiles, capteurs, etc.), de grandes quantités de données localisées dans l'espace et dans le temps sont désormais disponibles. Les bases de données associées peuvent être qualifiées de bases de données spatio-temporelles car chaque donnée est décrite par une information spatiale (e.g. une ville, un quartier, une rivière, etc.) et temporelle (p. ex. la date d'un événement). Cette masse de données souvent hétérogènes et complexes génère ainsi de nouveaux besoins auxquels les méthodes d'extraction de connaissances doivent pouvoir répondre (e.g. suiv
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50

Ferraro, Gabriela. "Towards deep content extraction from specialized discourse : the case of verbal relations in patent claims." Doctoral thesis, Universitat Pompeu Fabra, 2012. http://hdl.handle.net/10803/84174.

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This thesis addresses the problem of the development of Natural Language Processing techniques for the extraction and generalization of compositional and functional relations from specialized written texts and, in particular, from patent claims. One of the most demanding tasks tackled in the thesis is, according to the state of the art, the semantic generalization of linguistic denominations of relations between object components and processes described in the texts. These denominations are usually verbal expressions or nominalizations that are too concrete to be used as standard labels
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