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