| A study of factors affecting the utility of implicit relevance feedback |
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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: Relevance feedback
table of contents
Pages: 35 - 42
Year of Publication: 2005
ISBN:1-59593-034-5
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Downloads (6 Weeks): 10, Downloads (12 Months): 115, Citation Count: 14
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ABSTRACT
Implicit relevance feedback (IRF) is the process by which a search system unobtrusively gathers evidence on searcher interests from their interaction with the system. IRF is a new method of gathering information on user interest and, if IRF is to be used in operational IR systems, it is important to establish when it performs well and when it performs poorly. In this paper we investigate how the use and effectiveness of IRF is affected by three factors: search task complexity, the search experience of the user and the stage in the search. Our findings suggest that all three of these factors contribute to the utility of IRF.
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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[doi> 10.1145/332040.332440]
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CITED BY 14
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Thorsten Joachims , Laura Granka , Bing Pan , Helene Hembrooke , Filip Radlinski , Geri Gay, Evaluating the accuracy of implicit feedback from clicks and query reformulations in Web search, ACM Transactions on Information Systems (TOIS), v.25 n.2, p.7-es, April 2007
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Ian Ruthven , Mark Baillie , Leif Azzopardi , Ralf Bierig , Emma Nicol , Simon Sweeney , Murat Yaciki, Contextual factors affecting the utility of surrogates within exploratory search, Information Processing and Management: an International Journal, v.44 n.2, p.437-462, March, 2008
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Hila Becker , Christopher Meek , David Maxwell Chickering, Modeling contextual factors of click rates, Proceedings of the 22nd national conference on Artificial intelligence, p.1310-1315, July 22-26, 2007, Vancouver, British Columbia, Canada
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