基于矩阵分解的伪相关反馈技术<sup>*</sup>

doi:10.16451/j.cnki.issn1003-6059.201508009

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Abstract The performance of pseudo-relevance feedback technique is heavily dependent on two parameter values. Under the lack of relevance valuation results, these parameters can only rely on experience to set. In this paper, a pseudo-relevance feedback technique based on matrix factorization is proposed. This technique fuses multiple pseudo-relevance feedback results using the ideas of collaborative filtering together. And the optimal parameters are automatically selected for query expansion. Experimental results show that compared with the existing pseudo-relevance feedback techniques, the proposed method has a better retrieval performance, regardless of any underlying information retrieval model.

Key words： Pseudo-Relevance Feedback Matrix Factorization Query Expansion Collaborative Filtering

Received: 03 September 2014

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	Articles by authors
	ZHOU Dong
	LIU Jian-Xun
	ZHANG San-Rong

Cite this article:

ZHOU Dong,LIU Jian-Xun,ZHANG San-Rong. Pseudo-Relevance Feedback Technique Based on Matrix Factorization[J]. , 2015, 28(8): 735-740.

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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201508009 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2015/V28/I8/735

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