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Issue No. 08 - August (2007 vol. 40)
ISSN: 0018-9162
pp: 34-40
Thorsten Joachims , Cornell University
Filip Radlinski , Cornell University
ABSTRACT
Search-engine logs provide a wealth of information that machine-learning techniques can harness to improve search quality. With proper interpretations that avoid inherent biases, a search engine can use training data extracted from the logs to automatically tailor ranking functions to a particular user group or collection.
INDEX TERMS
search, pairwise preferences, Osmot engine, machine learning
CITATION

T. Joachims and F. Radlinski, "Search Engines that Learn from Implicit Feedback," in Computer, vol. 40, no. , pp. 34-40, 2007.
doi:10.1109/MC.2007.289
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