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2010
ACM

Estimation of statistical translation models based on mutual information for ad hoc information retrieval

9 years 5 months ago
Estimation of statistical translation models based on mutual information for ad hoc information retrieval
As a principled approach to capturing semantic relations of words in information retrieval, statistical translation models have been shown to outperform simple document language models which rely on exact matching of words in the query and documents. A main challenge in applying translation models to ad hoc information retrieval is to estimate a translation model without training data. Existing work has relied on training on synthetic queries generated based on a document collection. However, this method is computationally expensive and does not have a good coverage of query words. In this paper, we propose an alternative way to estimate a translation model based on normalized mutual information between words, which is less computationally expensive and has better coverage of query words than the synthetic query method of estimation. We also propose to regularize estimated translation probabilities to ensure sufficient probability mass for self-translation. Experiment results show tha...
Maryam Karimzadehgan, ChengXiang Zhai
Added 16 Aug 2010
Updated 16 Aug 2010
Type Conference
Year 2010
Where SIGIR
Authors Maryam Karimzadehgan, ChengXiang Zhai
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