Framework of Bert-Based and Attention-Based Networks for Community Question Answering Tasks

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dc.contributor.advisorHuang, Jimmy
dc.contributor.authorZhao, Xuan
dc.date.accessioned2021-11-15T15:19:09Z
dc.date.available2021-11-15T15:19:09Z
dc.date.copyright2021-05
dc.date.issued2021-11-15
dc.date.updated2021-11-15T15:19:09Z
dc.degree.disciplineElectrical and Computer Engineering
dc.degree.levelMaster's
dc.degree.nameMASc - Master of Applied Science
dc.description.abstractCommunity question answering (CQA) becomes increasingly prevalent in recent years, providing platforms for users with various background to obtain information and share knowledge. However, there are a large number of answers, difficult for users to view item by item and select the most relevant one. Therefore, answer selection and duplicate question detection become very significant subtask of CQA. In this work, we propose different models to explore these tasks. First, we study the correlation between question and paired answer. Then, we introduce the attention-based model Himu-QAAN for the answer selection task. Also, we present a BERT-based model Bert-QAnet for duplicate question detection task. We test our methods on various datasets. The results show that our methods achieve significant performance.
dc.identifier.urihttp://hdl.handle.net/10315/38666
dc.languageen
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.subjectComputer science
dc.subject.keywordsCommunity question answering
dc.subject.keywordsAttention networks
dc.subject.keywordsBERT
dc.titleFramework of Bert-Based and Attention-Based Networks for Community Question Answering Tasks
dc.typeElectronic Thesis or Dissertation

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