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Question answering over knowledge bases( QA-KB) was committed to analyzing user's query intent more accurately,then returned more concise and accurate results to questions asked by natural language. Most of existing QA-KB methods were based on APA( alignment-prediction-answering) framework,which separated the whole process of QA into several independent parts and used greedy algorithm to support the decision process. To overcome the lack of integrity and accuracy,a end-to-end unsupervised QA-KB model based on dynamic programming algorithm was proposed,and its capacity was proved on QA datasets,particularly on Chinese datasets containing multi-hop questions,by experiments.
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Basic Information:
DOI：10.13705/j.issn.1671-6841.2018298
China Classification Code:TP391.1;O221.3
Citation Information:
[1]WANG Yue,ZHANG Richong,BDBC and SKLSDE,School of Computer Science and Engineering,Beihang University.Question Answering Over Knowledge Base with Dynamic Programming[J].Journal of Zhengzhou University(Natural Science Edition),2019,51(04):37-42.DOI:10.13705/j.issn.1671-6841.2018298.
Fund Information:
国家自然科学基金项目(61772059,61421003)
2018-11-07
2018
2019-06-20
2019-11-08
2019
2
2019-08-06
2019-08-06
2019-08-06