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Relevance weighting for query independent evidence
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Source Annual ACM Conference on Research and Development in Information Retrieval archive
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
Authors
Nick Craswell  Microsoft Research, Cambridge, U.K.
Stephen Robertson  Microsoft Research, Cambridge, U.K.
Hugo Zaragoza  Microsoft Research, Cambridge, U.K.
Michael Taylor  Microsoft Research, Cambridge, U.K.
Sponsor
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
Bibliometrics
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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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.


Collaborative Colleagues:
Nick Craswell: colleagues
Stephen Robertson: colleagues
Hugo Zaragoza: colleagues
Michael Taylor: colleagues