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Informatics Report Series
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| Title:Relevance-Based Language Models |
| Authors:
Victor Lavrenko
; W.B. Croft
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| Date:Sep 2001 |
| Publication Title:Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval |
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Publication Type:Conference Paper
Publication Status:Published
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Page Nos:120-127
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DOI:10.1145/383952.383972
ISBN/ISSN:1-58113-331-6
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- Abstract:
- We explore the relation between classical probabilistic models of information retrieval and the emerging language modeling approaches. It has long been recognized that the primary obstacle to effective performance of classical models is the need to estimate a relevance model: probabilities of words in the relevant class. We propose a novel technique for estimating these probabilities using the query alone. We demonstrate that our technique can produce highly accurate relevance models, addressing important notions of synonymy and polysemy. Our experiments show relevance models outperforming baseline language modeling systems on TREC retrieval and TDT tracking tasks. The main contribution of this work is an effective formal method for estimating a relevance model with no training data.
- Links To Paper
- No links available
- Bibtex format
- @InProceedings{EDI-INF-RR-1190,
- author = {
Victor Lavrenko
and W.B. Croft
},
- title = {Relevance-Based Language Models},
- book title = {Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval},
- year = 2001,
- month = {Sep},
- pages = {120-127},
- doi = {10.1145/383952.383972},
- }
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