Learning the Multilingual Translation Representations for Question Retrieval in Community Question Answering via Non-Negative Matrix Factorization

doi:10.1109/TASLP.2016.2544661

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 自然语言处理团队

	Learning the Multilingual Translation Representations for Question Retrieval in Community Question Answering via Non-Negative Matrix Factorization
	Zhou, Guangyou 1; Xie, Zhiwen 1; He, Tingting 1; Zhao, Jun1,2 ; Hu, Xiaohua Tony 1,3
刊名	IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING
	2016-07-01
卷号	24 期号:7 页码:1305-1314
关键词	Natural Language Processing Information Retrieval Community Question Answering Question Retrieval Text Mining
DOI	10.1109/TASLP.2016.2544661
文献子类	Article
英文摘要	Community question answering (CQA) has become an increasingly popular research topic. In this paper, we focus on the problem of question retrieval. Question retrieval in CQA can automatically find the most relevant and recent questions that have been solved by other users. However, the word ambiguity and word mismatch problems bring about new challenges for question retrieval in CQA. State-of-the-art approaches address these issues by implicitly expanding the queried questions with additional words or phrases using monolingual translation models. While useful, the effectiveness of these models is highly dependent on the availability of quality parallel monolingual corpora (e. g., question-answer pairs) in the absence of which they are troubled by noise issues. In this work, we propose an alternative way to address the word ambiguity and word mismatch problems by taking advantage of potentially rich semantic information drawn from other languages. Our proposed method employs statistical machine translation to improve question retrieval and enriches the question representation with the translated words from other languages via non-negative matrix factorization. Experiments conducted on real CQA data sets show that our proposed approach is promising.
WOS关键词	MODEL
WOS研究方向	Acoustics ; Engineering
语种	英语
WOS记录号	WOS:000377455600001
资助机构	National Natural Science Foundation of China(61303180 ; 61573163)
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/12182]
专题	自动化研究所_模式识别国家重点实验室_自然语言处理团队
作者单位	1.Cent China Normal Univ, Sch Comp Sci, Wuhan 430079, Peoples R China 2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100080, Peoples R China 3.Drexel Univ, Coll Comp & Informat, Philadelphia, PA 19104 USA
推荐引用方式 GB/T 7714	Zhou, Guangyou,Xie, Zhiwen,He, Tingting,et al. Learning the Multilingual Translation Representations for Question Retrieval in Community Question Answering via Non-Negative Matrix Factorization[J]. IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,2016,24(7):1305-1314.
APA	Zhou, Guangyou,Xie, Zhiwen,He, Tingting,Zhao, Jun,&Hu, Xiaohua Tony.(2016).Learning the Multilingual Translation Representations for Question Retrieval in Community Question Answering via Non-Negative Matrix Factorization.IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING,24(7),1305-1314.
MLA	Zhou, Guangyou,et al."Learning the Multilingual Translation Representations for Question Retrieval in Community Question Answering via Non-Negative Matrix Factorization".IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING 24.7(2016):1305-1314.