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A Model of Vietnamese person named entity question answering system
Proceedings of the 26th Pacific Asia Conference on Language, Information and Computation, PACLIC 2012 Số , năm 2012 (Tập , trang 325-332)
DOI:
Tài liệu thuộc danh mục: Scopus
Conference Paper
English
Từ khóa: Answer extraction; QA; Question analysis; Question parser; Vietnamese; VPQA; Learning algorithms; Search engines; Natural language processing systems
Tóm tắt tiếng anh
In this paper, we proposed a Vietnamese named entity question answering (QA) model. This model applies an analytical question method using CRF machine learning algorithm combined with two automatic answering strategies: indexed sentences database-based and Google search engine-based. We gathered a Vietnamese question dataset containing about 2000 popular "Who, Whom, Whose" questions to evaluate our question chunking method and QA model. According to experiments, question chunking phase acquired the average F1 score of 92.99%. Equally significant, in our QA evaluation, experimental results illustrated that our approaches were completely reasonable and realistic with 74.63% precision and 87.9% ability to give the answers. � 2012 The PACLIC.
