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Issue No.08 - August (2007 vol.40)
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
Thorsten Joachims, Filip Radlinski, "Search Engines that Learn from Implicit Feedback", Computer, vol.40, no. 8, pp. 34-40, August 2007, doi:10.1109/MC.2007.289
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