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

Bruza, Peter; Song, Dawei

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)
• 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)
• Peer Reviewed: Peer Reviewed
• 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
• Contract Date: May 25, 2009