CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
A Joint Model for Question Answering over Multiple Knowledge Bases
Yuanzhe Zhang; Shizhu He; Kang Liu; Jun Zhao
2016-02
Conference NameThe Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016)
Conference DateFeb 12, 2016 - Feb 17, 2016
Conference PlacePhoenix, USA
Abstract

As the amount of knowledge bases (KBs) grows rapidly, the problem of question answering (QA) over multiple KBs has drawn more attention. The most significant distinction between multiple KB-QA and single KB-QA is that the former must consider the alignments between KBs. The pipeline strategy first constructs the alignments independently, and then uses the obtained alignments to construct queries. However, alignment construction is not a trivial task, and the introduced noises would be passed on to query construction. By contrast, we notice that alignment construction and query construction are interactive steps, and jointly considering them would be beneficial. To this end, we present a novel joint model based on integer linear programming (ILP), uniting these two procedures into a uniform framework. The experimental results demonstrate that the proposed approach outperforms state-of-the-art systems, and is able to improve the performance of both alignment construction and query construction.

Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/40600
Collection模式识别国家重点实验室_自然语言处理
Corresponding AuthorYuanzhe Zhang
AffiliationNational Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
First Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Corresponding Author AffilicationChinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Yuanzhe Zhang,Shizhu He,Kang Liu,et al. A Joint Model for Question Answering over Multiple Knowledge Bases[C],2016.
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