[1]ZHANG Tao,JIA Zhen,LI Tianrui,et al.Open-domain question-answering system based on large-scale knowledge base[J].CAAI Transactions on Intelligent Systems,2018,13(4):557-563.[doi:10.11992/tis.201707039]
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Open-domain question-answering system based on large-scale knowledge base

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 13 Number of periods: 2018 4 Page number: 557-563 Column: 学术论文—知识工程 Public date: 2018-07-05
Title:
Open-domain question-answering system based on large-scale knowledge base
Author(s):
ZHANG Tao;  JIA Zhen;  LI Tianrui;  HUANG Yanyong
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China
Keywords:
question-answering system; open domain; entity recognition; entity linking; knowledge base
CLC:
TP391.1
DOI:
10.11992/tis.201707039
Abstract:
Question-answering (QA) systems can understand user questions and return answers directly. Currently, most QA systems can only answer questions pertaining to specific domains. In this paper, we propose a method for constructing an open-domain QA system based on a large-scale knowledge base. First, we present an approach based on a visual dictionary and a conditional random field (CRF) model to identify the subject in question. Next, we use a fuzzy matching method to link the entity in question to that in the knowledge base, and apply similarity computation and rule matching methods to recognize the question predicates and link them to the attributes of the knowledge entity. Lastly, we implement entity disambiguation and answer retrieval. The mean F-measure value of the proposed system is 0.695 6, which indicates the feasibility of the proposed method for an open-domain QA system for a large-scale knowledge base.
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