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

作者：

Highlights：

• 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.

摘要

•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.

论文关键词：Dictionary-based cross-language information retrieval,Query translation,Expectation maximization,Pseudo-relevant documents,00-01,99-00

论文评审过程：Received 10 January 2016, Revised 23 November 2016, Accepted 25 November 2016, Available online 9 December 2016, Version of Record 9 December 2016.

论文官网地址：https://doi.org/10.1016/j.ipm.2016.11.007