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Identifier 000421549
Title Open domain question answering over hundreds of linked open datasets
Alternative Title Aπάντηση ερωτήσεων ανοιχτού πεδίου πάνω από εκατοντάδες ανοιχτά συνδεδεμένα σύνολα δεδομένων
Author Δημητράκης, Ελευθέριος Θ.
Thesis advisor Τζίτζικας, Γιάννης
Reviewer Πλεξουσάκης, Δημήτρης
Φλουρής, Γεώργιος
Abstract Open domain Question Answering is a challenging task that requires, among others, to tackle the data distribution issue, i.e. the fact that datasets are scattered in several places. In this thesis, we focus on open domain Question Answering over Linked Open Data. We confine ourselves to three kinds of questions: factoid, confirmation, and definition questions. We introduce and comparatively evaluate information extraction based processes for question answering. The distinctive feature of our approach is that it can answer questions over millions of entities, by exploiting hundreds of Linked Data sources simultaneously, without having to use any training data. The process comprises three main phases: (i) Question Analysis (that includes question type identification and cleaning), (ii) Entities Detection, Named Entity recognition and linking and (iii) Answer Extraction (that includes RDF triples retrieval, scoring and matching). We demonstrate the benefits of this approach in terms of answerable questions and answer verification, and we investigate, through experimental results, how the steps of the question answering process affect the effectiveness of question answering. The evaluation was based on 1000 questions from SimpleQuestions and 2500 from QALD-7 Largescale datasets.
Language English
Subject Factoid questions
Open domain
Question answering
Ανοιχτό πεδίο
Απάντηση ερωτήσεων
Ερωτήσεις γεγονότων
Issue date 2019-03-29
Collection   Faculty/Department--Faculty of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/5/e/7/metadata-dlib-1552037158-385984-27635.tkl Bookmark and Share
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