A chinese question answering approach integrating count-based and embedding-based features

Benyou Wang; Jiabin Niu; Liqun Ma; Yuhua Zhang; Lipeng Zhang; Jingfei Li; Peng Zhang; Dawei Song

doi:10.1007/978-3-319-50496-4_88

A chinese question answering approach integrating count-based and embedding-based features

Benyou Wang, Jiabin Niu, Liqun Ma, Yuhua Zhang, Lipeng Zhang, Jingfei Li, Peng Zhang^*, Dawei Song

^*此作品的通讯作者

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

10 引用（Scopus）

摘要

Document-based Question Answering system, which needs to match semantically the short text pairs, has gradually become an important topic in the fields of natural language processing and information retrieval. Question Answering system based on English corpus has developed rapidly with the utilization of the deep learning technology, whereas an effective Chinese-customized system needs to be paid more attention. Thus, we explore a Question Answering system which is characterized in Chinese for the QA task of NLPCC. In our approach, the ordered sequential information of text and deep matching of semantics of Chinese textual pairs have been captured by our count-based traditional methods and embedding-based neural network. The ensemble strategy has achieved a good performance which is much stronger than the provided baselines.

源语言	英语
主期刊名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
出版商	Springer Verlag
页	934-941
页数	8
DOI	https://doi.org/10.1007/978-3-319-50496-4_88
出版状态	已出版 - 1 12月 2016
已对外发布	是

出版系列

姓名	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
卷	10102
ISSN（印刷版）	0302-9743
ISSN（电子版）	1611-3349

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10.1007/978-3-319-50496-4_88

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Wang, B., Niu, J., Ma, L., Zhang, Y., Zhang, L., Li, J., Zhang, P., & Song, D. (2016). A chinese question answering approach integrating count-based and embedding-based features. 在 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (页码 934-941). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10102). Springer Verlag. https://doi.org/10.1007/978-3-319-50496-4_88

Wang, Benyou ; Niu, Jiabin ; Ma, Liqun 等. / A chinese question answering approach integrating count-based and embedding-based features. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2016. 页码 934-941 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A chinese question answering approach integrating count-based and embedding-based features",

abstract = "Document-based Question Answering system, which needs to match semantically the short text pairs, has gradually become an important topic in the fields of natural language processing and information retrieval. Question Answering system based on English corpus has developed rapidly with the utilization of the deep learning technology, whereas an effective Chinese-customized system needs to be paid more attention. Thus, we explore a Question Answering system which is characterized in Chinese for the QA task of NLPCC. In our approach, the ordered sequential information of text and deep matching of semantics of Chinese textual pairs have been captured by our count-based traditional methods and embedding-based neural network. The ensemble strategy has achieved a good performance which is much stronger than the provided baselines.",

keywords = "Chinese text, DBQA, Question answer, Semantic matching",

author = "Benyou Wang and Jiabin Niu and Liqun Ma and Yuhua Zhang and Lipeng Zhang and Jingfei Li and Peng Zhang and Dawei Song",

note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2016.",

year = "2016",

month = dec,

day = "1",

doi = "10.1007/978-3-319-50496-4_88",

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Wang, B, Niu, J, Ma, L, Zhang, Y, Zhang, L, Li, J, Zhang, P & Song, D 2016, A chinese question answering approach integrating count-based and embedding-based features. 在 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 10102, Springer Verlag, 页码 934-941. https://doi.org/10.1007/978-3-319-50496-4_88

A chinese question answering approach integrating count-based and embedding-based features. / Wang, Benyou; Niu, Jiabin; Ma, Liqun 等.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag, 2016. 页码 934-941 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 10102).

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

TY - CHAP

T1 - A chinese question answering approach integrating count-based and embedding-based features

AU - Wang, Benyou

AU - Niu, Jiabin

AU - Ma, Liqun

AU - Zhang, Yuhua

AU - Zhang, Lipeng

AU - Li, Jingfei

AU - Zhang, Peng

AU - Song, Dawei

PY - 2016/12/1

Y1 - 2016/12/1

N2 - Document-based Question Answering system, which needs to match semantically the short text pairs, has gradually become an important topic in the fields of natural language processing and information retrieval. Question Answering system based on English corpus has developed rapidly with the utilization of the deep learning technology, whereas an effective Chinese-customized system needs to be paid more attention. Thus, we explore a Question Answering system which is characterized in Chinese for the QA task of NLPCC. In our approach, the ordered sequential information of text and deep matching of semantics of Chinese textual pairs have been captured by our count-based traditional methods and embedding-based neural network. The ensemble strategy has achieved a good performance which is much stronger than the provided baselines.

AB - Document-based Question Answering system, which needs to match semantically the short text pairs, has gradually become an important topic in the fields of natural language processing and information retrieval. Question Answering system based on English corpus has developed rapidly with the utilization of the deep learning technology, whereas an effective Chinese-customized system needs to be paid more attention. Thus, we explore a Question Answering system which is characterized in Chinese for the QA task of NLPCC. In our approach, the ordered sequential information of text and deep matching of semantics of Chinese textual pairs have been captured by our count-based traditional methods and embedding-based neural network. The ensemble strategy has achieved a good performance which is much stronger than the provided baselines.

KW - Chinese text

KW - DBQA

KW - Question answer

KW - Semantic matching

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AN - SCOPUS:85003944986

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 934

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BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

PB - Springer Verlag

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Wang B, Niu J, Ma L, Zhang Y, Zhang L, Li J 等. A chinese question answering approach integrating count-based and embedding-based features. 在 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Verlag. 2016. 页码 934-941. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-50496-4_88

A chinese question answering approach integrating count-based and embedding-based features

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