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A comparison of various approaches for using probabilistic dependencies in language modeling.

Bruza, Peter; Song, Dawei

Authors

Peter Bruza

Dawei Song



Abstract

The goals of this article is to study several estimates of relevance models which will be computed based on differing approaches for incorporating term dependency information. In this way, we hope to shed light on the relative merits of term dependency information, as well as provide a theoretical framework for such investigations.

Citation

BRUZA, P. and SONG, D. 2003. A comparison of various approaches for using probabilistic dependencies in language modeling. In Proceedings of the 26th Annual international Association of Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR) conference on research and development in information retrieval (SIGIR'03), 28 July - 1 August 2003, Toronto, Canada. New York: ACM [online], pages 419-420. Available from: https://doi.org/10.1145/860435.860530

Presentation Conference Type Poster
Conference Name 26th Annual international Association of Computing Machinery Special Interest Group on Information Retrieval (ACM SIGIR) conference on research and development in information retrieval (SIGIR'03)
Conference Location Toronto, Canada
Start Date Jul 28, 2003
End Date Aug 1, 2003
Deposit Date May 25, 2009
Publicly Available Date May 25, 2009
Publisher Association for Computing Machinery (ACM)
Pages 419-420
DOI https://doi.org/10.1145/860435.860530
Keywords Probabilistic tendencies; Hyperspace analogue to language; Information flow
Public URL http://hdl.handle.net/10059/342

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