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Dissertations / Theses on the topic 'Relation extraction'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

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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2

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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3

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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4

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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5

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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6

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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7

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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8

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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9

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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10

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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11

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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12

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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13

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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14

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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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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16

Al, Qady Mohammed Abdelrahman. "Concept relation extraction using natural language processing the CRISP technique /." [Ames, Iowa : Iowa State University], 2008.

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17

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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18

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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20

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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21

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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22

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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23

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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24

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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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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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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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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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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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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Ebadat, Ali-Reza. "Toward Robust Information Extraction Models for Multimedia Documents." Phd thesis, INSA de Rennes, 2012. http://tel.archives-ouvertes.fr/tel-00760383.

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Au cours de la dernière décennie, d'énormes quantités de documents multimédias ont été générées. Il est donc important de trouver un moyen de gérer ces données, notamment d'un point de vue sémantique, ce qui nécessite une connaissance fine de leur contenu. Il existe deux familles d'approches pour ce faire, soit par l'extraction d'informations à partir du document (par ex., audio, image), soit en utilisant des données textuelles extraites du document ou de sources externes (par ex., Web). Notre travail se place dans cette seconde famille d'approches ; les informations extraites des textes peuve

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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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Pareti, Silvia. "Attribution : a computational approach." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/14170.

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Our society is overwhelmed with an ever growing amount of information. Effective management of this information requires novel ways to filter and select the most relevant pieces of information. Some of this information can be associated with the source or sources expressing it. Sources and their relation to what they express affect information and whether we perceive it as relevant, biased or truthful. In news texts in particular, it is common practice to report third-party statements and opinions. Recognizing relations of attribution is therefore a necessary step toward detecting statements a

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Akbik, Alan [Verfasser], Volker [Akademischer Betreuer] Markl, Hans [Gutachter] Uszkoreit, and Chris [Gutachter] Biemann. "Exploratory relation extraction in large multilingual data / Alan Akbik ; Gutachter: Hans Uszkoreit, Chris Biemann ; Betreuer: Volker Markl." Berlin : Technische Universität Berlin, 2016. http://d-nb.info/1156177308/34.

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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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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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Byrne, Kate. "Populating the Semantic Web : combining text and relational databases as RDF graphs." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3781.

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The Semantic Web promises a way of linking distributed information at a granular level by interconnecting compact data items instead of complete HTML pages. New data is gradually being added to the Semantic Web but there is a need to incorporate existing knowledge. This thesis explores ways to convert a coherent body of information from various structured and unstructured formats into the necessary graph form. The transformation work crosses several currently active disciplines, and there are further research questions that can be addressed once the graph has been built. Hybrid databases, such

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Eichler, Kathrin [Verfasser], and Josef van [Akademischer Betreuer] Genabith. "Generating and applying textual entailment graphs for relation extraction and email categorization / Kathrin Eichler ; Betreuer: Josef van Genabith." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2018. http://d-nb.info/1162892242/34.

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Hallström, Eric. "Relation Extraction on Swedish Text by the Use of Semantic Fields and Deep Multi-Channel Convolutional Neural Networks." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262494.

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This thesis makes two contributions to the research domain of relation extraction (RE), i.e., the automated discovery of semantic links in unstructured text. The first contribution is a method for creating a dataset for RE, and using it to create the first Swedish RE dataset involving nine relationships between persons, locations and vehicles. The second contribution is a variety of experiments on this new dataset providing baselines. The relation extraction systems created in this thesis include deep multi-channel convolutional neural networks, and Word2Vec embeddings. A manual labeling of a

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Thomas, Philippe. "Robust relationship extraction in the biomedical domain." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2015. http://dx.doi.org/10.18452/17372.

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Seit Jahrhunderten wird menschliches Wissen in Form von natürlicher Sprache ausgetauscht und in Dokumenten schriftlich aufgezeichnet. In den letzten Jahren konnte man auf dem Gebiet der Lebenswissenschaften eine exponentielle Zunahme wissenschaftlicher Publikationen beobachten. Diese Dissertation untersucht die automatische Extraktion von Beziehungen zwischen Eigennamen. Innerhalb dieses Gebietes beschäftigt sich die Arbeit mit der Steigerung der Robustheit für die Relationsextraktion. Zunächst wird der Einsatz von Ensemble-Methoden anhand von Daten aus der "Drug-drug-interaction challenge 20

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Krause, Sebastian [Verfasser], Volker [Akademischer Betreuer] Markl, Hans [Akademischer Betreuer] Uszkoreit, Hans [Gutachter] Uszkoreit, Volker [Gutachter] Markl, and Shinichi [Gutachter] Nakajima. "Knowledge-intensive, high-performance relation extraction / Sebastian Krause ; Gutachter: Hans Uszkoreit, Volker Markl, Shinichi Nakajima ; Volker Markl, Hans Uszkoreit." Berlin : Technische Universität Berlin, 2018. http://d-nb.info/1156331277/34.

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Brudieux, Véronique. "Extraction, modification enzymatique et caractérisation chimique de nouvelles structures pectiques : application de la relation structure/activité à la dermocosmétique." Limoges, 2007. https://aurore.unilim.fr/theses/nxfile/default/7d830b54-6fee-461e-8c54-9cd84e773544/blobholder:0/2007LIMO4060.pdf.

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Les polysaccharides et plus particulièrement les pectines sont des molécules d'intérêt biologique dont nos travaux démontrent qu'elles peuvent être utilisées par l'industrie dermocosmétique. C'est sur ce thème que la société SILAB et le Laboratoire de Chimie des Substances Naturelles ont décidé d'engager une étude prospective. Dans une première partie, nous nous sommes intéressés au rhamnogalacturonane de type I dont la variabilité chimique a été approchée après screening réalisé sur 11 matières végétales. Les protocoles ont été transférés puis optimisés à une échelle permettant, pour trois de

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Genest, Pierre-Yves. "Unsupervised open-world information extraction from unstructured and domain-specific document collections." Electronic Thesis or Diss., Lyon, INSA, 2024. http://www.theses.fr/2024ISAL0111.

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La croissance exponentielle de la production de données a fait de l’analyse de collections de documents textuels non structurés un défi majeur. Cette thèse de doctorat vise à relever ce défi en se concentrant sur l’extraction d’information (IE), qui englobe quatre tâches principales : reconnaissance d’entités nommées (NER), résolution des coréférences (CR), annotation sémantique (EL) et extraction de relations (RE). Ces tâches permettent d’extraire et de structurer des connaissances à partir de documents non formatés, ce qui facilite leur intégration dans des bases de données structurées et le

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Gerber, Daniel. "Statistical Extraction of Multilingual Natural Language Patterns for RDF Predicates: Algorithms and Applications." Doctoral thesis, Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-208759.

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The Data Web has undergone a tremendous growth period. It currently consists of more then 3300 publicly available knowledge bases describing millions of resources from various domains, such as life sciences, government or geography, with over 89 billion facts. In the same way, the Document Web grew to the state where approximately 4.55 billion websites exist, 300 million photos are uploaded on Facebook as well as 3.5 billion Google searches are performed on average every day. However, there is a gap between the Document Web and the Data Web, since for example knowledge bases available on the D

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Alt, Christoph Benedikt [Verfasser], Sebastian [Akademischer Betreuer] Möller, Sebastian [Gutachter] Möller, Hans [Gutachter] Uszkoreit, and Alan [Gutachter] Akbik. "Neural sequential transfer learning for relation extraction / Christoph Benedikt Alt ; Gutachter: Sebastian Möller, Hans Uszkoreit, Alan Akbik ; Betreuer: Sebastian Möller." Berlin : Technische Universität Berlin, 2021. http://d-nb.info/1225792797/34.

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Hänig, Christian. "Unsupervised Natural Language Processing for Knowledge Extraction from Domain-specific Textual Resources." Doctoral thesis, Universitätsbibliothek Leipzig, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-112706.

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This thesis aims to develop a Relation Extraction algorithm to extract knowledge out of automotive data. While most approaches to Relation Extraction are only evaluated on newspaper data dealing with general relations from the business world their applicability to other data sets is not well studied. Part I of this thesis deals with theoretical foundations of Information Extraction algorithms. Text mining cannot be seen as the simple application of data mining methods to textual data. Instead, sophisticated methods have to be employed to accurately extract knowledge from text which then can b

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Konstantinova, Natalia. "Knowledge acquisition from user reviews for interactive question answering." Thesis, University of Wolverhampton, 2013. http://hdl.handle.net/2436/297401.

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Nowadays, the effective management of information is extremely important for all spheres of our lives and applications such as search engines and question answering systems help users to find the information that they need. However, even when assisted by these various applications, people sometimes struggle to find what they want. For example, when choosing a product customers can be confused by the need to consider many features before they can reach a decision. Interactive question answering (IQA) systems can help customers in this process, by answering questions about products and initiatin

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Bendjama, Zoubida. "Extraction d'acétate d'éthyle de solutions aqueuses par pervaporation à travers des membranes en polydimethylsiloxane comportant divers degrés de réticulation." Vandoeuvre-les-Nancy, INPL, 1993. http://www.theses.fr/1993INPL030N.

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Parmi les domaines d'investigation concernant la pervaporation, nous avons choisi d'étudier l'extraction de substances organiques volatiles de milieux aqueux à travers un matériau polymère: le polydimethylsiloxane (PDMS). Le transfert pervaporatif d'un composé-type, l'acétate d'éthyle, a été modélisé. Le modèle établi permet la caractérisation des systèmes considérés à partir d'une seule opération de pervaporation. L'élaboration d'élastomères (PDMS), et la détermination de leurs propriétés physiques et mécaniques, nous ont permis de montrer que la dureté, le module d'élasticité, la température

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Rahman, Md Rashedur. "Knowledge Base Population based on Entity Graph Analysis." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS092/document.

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Le peuplement de base de connaissance (KBP) est une tâche importante qui présente de nombreux défis pour le traitement automatique des langues. L'objectif de cette tâche est d'extraire des connaissances de textes et de les structurer afin de compléter une base de connaissances. Nous nous sommes intéressés à la reconnaissance de relations entre entités. L'extraction de relations (RE) entre une paire de mentions d'entités est une tâche difficile en particulier pour les relations en domaine ouvert. Généralement, ces relations sont extraites en fonction des informations lexicales et syntaxiques au

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Fontecave, Jallon Julie. "Extraction semi-automatique des mouvements du tractus vocal à partir de données sinaradiographiques." Grenoble INPG, 2006. https://tel.archives-ouvertes.fr/tel-00203082.

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Nous proposons une technique pour faciliter l'extraction des contours du conduit vocal à partir de séquences cinéradiographiques de locuteurs. La méthode combine l'expertise humaine pour marquer manuellement un petit nombre d'images clefs et un traitement automatique de l'information vidéo (coefficient DCT basses fréquences des images). Nous estimons l'erreur de marquage. Pour chaque séquence les articulateurs (langue, lèvre, vélum,. . . ) sont traités indépendemment. Puis les contours obtenus sont combinés pour reconstruire le conduit vocal complet en mouvement. A partir de ces données, nous

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Miranda, Ackerman Eduardo Jacobo. "Extracting Causal Relations between News Topics from Distributed Sources." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-130066.

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The overwhelming amount of online news presents a challenge called news information overload. To mitigate this challenge we propose a system to generate a causal network of news topics. To extract this information from distributed news sources, a system called Forest was developed. Forest retrieves documents that potentially contain causal information regarding a news topic. The documents are processed at a sentence level to extract causal relations and news topic references, these are the phases used to refer to a news topic. Forest uses a machine learning approach to classify causal sentence

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