Turkish factoid question answering using answer pattern matching

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buir.advisorÇiçekli, İlyas
dc.contributor.authorPala Er, Nagehan
dc.date.accessioned2016-01-08T18:10:38Z
dc.date.available2016-01-08T18:10:38Z
dc.date.issued2009
dc.departmentDepartment of Computer Engineeringen_US
dc.descriptionAnkara : The Department of Computer Engineering and Information Science and the Institute of Engineering and Science of Bilkent University, 2009.en_US
dc.descriptionThesis (Master's) -- Bilkent University, 2009.en_US
dc.descriptionIncludes bibliographical references.en_US
dc.description.abstractEfficiently locating information on the Web has become one of the most important challenges in the last decade. The Web Search Engines have been used to locate the documents containing the required information. However, in many situations a user wants a particular piece of information rather than a document set. Question Answering (QA) systems have addressed this problem and they return explicit answers to questions rather than set of documents. Questions addressed by QA systems can be categorized into five categories: factoid, list, definition, complex, and speculative questions. A factoid question has exactly one correct answer, and the answer is mostly a named entity like person, date, or location. In this thesis, we develop a pattern matching approach for a Turkish Factoid QA system. In TREC-10 QA track, most of the question answering systems used sophisticated linguistic tools. However, the best performing system at the track used only an extensive list of surface patterns; therefore, we decided to investigate the potential of answer pattern matching approach for our Turkish Factoid QA system. We try different methods for answer pattern extraction such as stemming and named entity tagging. We also investigate query expansion by using answer patterns. Several experiments have been performed to evaluate the performance of the system. Compared with the results of the other factoid QA systems, our methods have achieved good results. The results of the experiments show that named entity tagging improves the performance of the system.en_US
dc.description.degreeM.S.en_US
dc.description.provenanceMade available in DSpace on 2016-01-08T18:10:38Z (GMT). No. of bitstreams: 1 0003846.pdf: 1762575 bytes, checksum: 65eb3d31be9da732b946685a0f43c2f6 (MD5)en
dc.description.statementofresponsibilityEr, Nagehan Palaen_US
dc.format.extentxvi, 155 leavesen_US
dc.identifier.itemidBILKUTUPB108611
dc.identifier.urihttp://hdl.handle.net/11693/14896
dc.language.isoEnglishen_US
dc.publisherBilkent Universityen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectFactoid question answeringen_US
dc.subjectPattern matchingen_US
dc.subjectQuery expansionen_US
dc.subject.lccQA76.9.Q4 E7 2009en_US
dc.subject.lcshQuestion-answering systems.en_US
dc.subject.lcshDatabase searching.en_US
dc.subject.lcshMatching theory.en_US
dc.titleTurkish factoid question answering using answer pattern matchingen_US
dc.typeThesisen_US

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Dept. of Computer Engineering - Master's degree