Semantic Comprehension of Questions in Q&A System for Chinese Language Based on Semantic Element Combination

Question understanding is an extremely important part of the question and answer (Q&A) system, which is the basis of subsequent information retrieval and answer extraction. In order to improve the semantic understanding of question, we propose a method of understanding the question based on the...
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Autor*in:	Jiaxing Song [verfasserIn] Feilong Liu [verfasserIn] Kai Ding [verfasserIn] Kai Du [verfasserIn] Xiaonan Zhang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Semantics system analysis and design logic testing

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 8(2020), Seite 102971-102981
Übergeordnetes Werk:	volume:8 ; year:2020 ; pages:102971-102981

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2020.2997958

Katalog-ID:	DOAJ069588236

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520			\|a Question understanding is an extremely important part of the question and answer (Q&A) system, which is the basis of subsequent information retrieval and answer extraction. In order to improve the semantic understanding of question, we propose a method of understanding the question based on the combination of semantic element for Chinese language. Firstly, the method uses lexical and rules recognition to extract the semantic elements of questions and recognizes the functions according to the preprocessing pattern. Secondly, combining the dependency analysis tree structure of the question and the function type, it can produce the semantic elements. Finally, a normalized semantic expression was generated. We extract the user questions in Baidu-Zhidao as the test set. The result shows that the accuracy of the proposed method is 97.8%, so the semantics of the Chinese language questions can be effectively understood by this method.
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allfieldsSound	10.1109/ACCESS.2020.2997958 doi (DE-627)DOAJ069588236 (DE-599)DOAJc3756f8adddf46ce83102ab4ff9c3a5d DE-627 ger DE-627 rakwb eng TK1-9971 Jiaxing Song verfasserin aut Semantic Comprehension of Questions in Q&A System for Chinese Language Based on Semantic Element Combination 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Question understanding is an extremely important part of the question and answer (Q&A) system, which is the basis of subsequent information retrieval and answer extraction. In order to improve the semantic understanding of question, we propose a method of understanding the question based on the combination of semantic element for Chinese language. Firstly, the method uses lexical and rules recognition to extract the semantic elements of questions and recognizes the functions according to the preprocessing pattern. Secondly, combining the dependency analysis tree structure of the question and the function type, it can produce the semantic elements. Finally, a normalized semantic expression was generated. We extract the user questions in Baidu-Zhidao as the test set. The result shows that the accuracy of the proposed method is 97.8%, so the semantics of the Chinese language questions can be effectively understood by this method. Semantics system analysis and design logic testing Electrical engineering. Electronics. Nuclear engineering Feilong Liu verfasserin aut Kai Ding verfasserin aut Kai Du verfasserin aut Xiaonan Zhang verfasserin aut In IEEE Access IEEE, 2014 8(2020), Seite 102971-102981 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:8 year:2020 pages:102971-102981 https://doi.org/10.1109/ACCESS.2020.2997958 kostenfrei https://doaj.org/article/c3756f8adddf46ce83102ab4ff9c3a5d kostenfrei https://ieeexplore.ieee.org/document/9102298/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 8 2020 102971-102981
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callnumber-first	T - Technology
author	Jiaxing Song
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topic_title	TK1-9971 Semantic Comprehension of Questions in Q&A System for Chinese Language Based on Semantic Element Combination Semantics system analysis and design logic testing
topic	misc TK1-9971 misc Semantics misc system analysis and design misc logic testing misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Semantics misc system analysis and design misc logic testing misc Electrical engineering. Electronics. Nuclear engineering
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title	Semantic Comprehension of Questions in Q&A System for Chinese Language Based on Semantic Element Combination
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title_sort	semantic comprehension of questions in q&a system for chinese language based on semantic element combination
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title_auth	Semantic Comprehension of Questions in Q&A System for Chinese Language Based on Semantic Element Combination
abstract	Question understanding is an extremely important part of the question and answer (Q&A) system, which is the basis of subsequent information retrieval and answer extraction. In order to improve the semantic understanding of question, we propose a method of understanding the question based on the combination of semantic element for Chinese language. Firstly, the method uses lexical and rules recognition to extract the semantic elements of questions and recognizes the functions according to the preprocessing pattern. Secondly, combining the dependency analysis tree structure of the question and the function type, it can produce the semantic elements. Finally, a normalized semantic expression was generated. We extract the user questions in Baidu-Zhidao as the test set. The result shows that the accuracy of the proposed method is 97.8%, so the semantics of the Chinese language questions can be effectively understood by this method.
abstractGer	Question understanding is an extremely important part of the question and answer (Q&A) system, which is the basis of subsequent information retrieval and answer extraction. In order to improve the semantic understanding of question, we propose a method of understanding the question based on the combination of semantic element for Chinese language. Firstly, the method uses lexical and rules recognition to extract the semantic elements of questions and recognizes the functions according to the preprocessing pattern. Secondly, combining the dependency analysis tree structure of the question and the function type, it can produce the semantic elements. Finally, a normalized semantic expression was generated. We extract the user questions in Baidu-Zhidao as the test set. The result shows that the accuracy of the proposed method is 97.8%, so the semantics of the Chinese language questions can be effectively understood by this method.
abstract_unstemmed	Question understanding is an extremely important part of the question and answer (Q&A) system, which is the basis of subsequent information retrieval and answer extraction. In order to improve the semantic understanding of question, we propose a method of understanding the question based on the combination of semantic element for Chinese language. Firstly, the method uses lexical and rules recognition to extract the semantic elements of questions and recognizes the functions according to the preprocessing pattern. Secondly, combining the dependency analysis tree structure of the question and the function type, it can produce the semantic elements. Finally, a normalized semantic expression was generated. We extract the user questions in Baidu-Zhidao as the test set. The result shows that the accuracy of the proposed method is 97.8%, so the semantics of the Chinese language questions can be effectively understood by this method.
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title_short	Semantic Comprehension of Questions in Q&A System for Chinese Language Based on Semantic Element Combination
url	https://doi.org/10.1109/ACCESS.2020.2997958 https://doaj.org/article/c3756f8adddf46ce83102ab4ff9c3a5d https://ieeexplore.ieee.org/document/9102298/ https://doaj.org/toc/2169-3536
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Semantic Comprehension of Questions in Q&A System for Chinese Language Based on Semantic Element Combination

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