A Joint Model for Question Answering over Multiple Knowledge Bases
Yuanzhe Zhang; Shizhu He; Kang Liu; Jun Zhao
2016-02
会议名称The Thirtieth AAAI Conference on Artificial Intelligence (AAAI 2016)
会议日期Feb 12, 2016 - Feb 17, 2016
会议地点Phoenix, USA
摘要

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.

收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/40600
专题多模态人工智能系统全国重点实验室_自然语言处理
通讯作者Yuanzhe Zhang
作者单位National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences
第一作者单位模式识别国家重点实验室
通讯作者单位模式识别国家重点实验室
推荐引用方式
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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