An expectation-maximization algorithm for query translation based on pseudo-relevant documents

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• 作者：Javid Dadashkarimi^a ; ^{dadashkarimi@ut.ac.ir} ; Azadeh Shakery ; ^a ; ^b ; ^{shakery@ut.ac.ir} ; Heshaam Faili^a ; ^b ; ^{hfaili@ut.ac.ir} ; Hamed Zamani¹ ; ^c ; ^{zamani@cs.umass.edu}
• 关键词：Dictionary-based cross-language information retrieval ; Query translation ; Expectation maximization ; Pseudo-relevant documents
• 刊名：Information Processing & Management
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：53
• 期：2
• 页码：371-387
• 全文大小：859 K
• 卷排序：53

文摘

A query translation method based on expectation maximization algorithm is proposed. The method (EM4QT) exploits pseudo-relevant documents in source and target languages. EM4QT extracts a number of hidden variables for each translation pair. EM4QT employs an expectation maximization algorithm for estimating the parameters. EM4QT outperforms competitive baselines in cross-language information retrieval.