| Relevance weighting for query independent evidence |
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Annual ACM Conference on Research and Development in Information Retrieval
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Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
table of contents
Salvador, Brazil
SESSION: Web search 2
table of contents
Pages: 416 - 423
Year of Publication: 2005
ISBN:1-59593-034-5
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Downloads (6 Weeks): 20, Downloads (12 Months): 144, Citation Count: 6
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ABSTRACT
A query independent feature, relating perhaps to document content, linkage or usage, can be transformed into a static, per-document relevance weight for use in ranking. The challenge is to find a good function to transform feature values into relevance scores. This paper presents FLOE, a simple density analysis method for modelling the shape of the transformation required, based on training data and without assuming independence between feature and baseline. For a new query independent feature, it addresses the questions: is it required for ranking, what sort of transformation is appropriate and, after adding it, how successful was the chosen transformation? Based on this we apply sigmoid transformations to PageRank, indegree, URL Length and ClickDistance, tested in combination with a BM25 baseline.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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N. Craswell and D. Hawking. Overview of the trec-2004 web track. In Proceedings of TREC-2004, Gaithersburg, Maryland USA, November 2004.
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Ronald Fagin , Ravi Kumar , Kevin S. McCurley , Jasmine Novak , D. Sivakumar , John A. Tomlin , David P. Williamson, Searching the workplace web, Proceedings of the 12th international conference on World Wide Web, May 20-24, 2003, Budapest, Hungary
[doi> 10.1145/775152.775204]
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T. Upstill. Document ranking using web evidence. PhD thesis, Australian National University, 2004.
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H. Zaragoza, N. Craswell, M. Taylor, S. Saria, and S. Robertson. Microsoft Cambridge at TREC--13: Web and HARD tracks. In Proceedings of TREC-2004, Gaithersburg, Maryland USA, November 2004.
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