Please use this identifier to cite or link to this item: https://hdl.handle.net/11264/1701
Full metadata record
DC FieldValueLanguage
dc.contributor.authorEnakoa, Anes-
dc.contributor.otherRoyal Military College of Canada / Collège militaire royal du Canadaen_US
dc.date.accessioned2019-04-29T14:53:44Z-
dc.date.accessioned2019-12-04T18:39:13Z-
dc.date.available2019-04-29T14:53:44Z-
dc.date.available2019-12-04T18:39:13Z-
dc.date.issued2019-04-29-
dc.identifier.urihttps://hdl.handle.net/11264/1701-
dc.description.abstractQuestion Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP) that is concerned with answering questions posed in a natural language. In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer Selection is one of the main components of the QA, which is responsible for selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging. To address this challenge, we propose an approach to answer questions with multiple answer choices for QA systems based on Textual Entailment (TE) recognition. The approach consists of combining three feature sets to evaluate whether one of the candidate answers can be inferred from the text returned by the system. Our system was designed to utilize information on the lexical, syntactic and semantic level in order to recognize the entailment between the generated hypotheses (H) and the text (T). For performance evaluation of our method, a set of experiments has been conducted on the dataset provided by CLEF 2012 through the task of QA4MRE. The obtained results show that our method helps significantly to tackle the problem of Answer Selection in Question Answering system.en_US
dc.language.isoenen_US
dc.subjectQuestion Answeringen_US
dc.titleAnswer Selection for Questions with Multiple-Answer-Choices in Question Answering System Based on Textual Entailment Recognitionen_US
dc.typeTheses-
dc.title.translatedSélection de réponses pour les questions à choix multiples en système de réponses aux questions fondées sur la reconnaissance de l’Implication textuelleen_US
dc.contributor.supervisorLiang, Yawei-
dc.date.acceptance2019-04-09-
thesis.degree.disciplineComputer Science/Sciences informatiquesen_US
thesis.degree.namePhD (Doctor of Philosophy/Doctorat en philosophie)en_US
Appears in Collections:Theses

Files in This Item:
File Description SizeFormat 
thesis.pdf5.11 MBAdobe PDFThumbnail
View/Open


Items in eSpace are protected by copyright, with all rights reserved, unless otherwise indicated.