Issue No. 08 - August (2007 vol. 40)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MC.2007.289
Thorsten Joachims , Cornell University
Filip Radlinski , Cornell University
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.
search, pairwise preferences, Osmot engine, machine learning
T. Joachims and F. Radlinski, "Search Engines that Learn from Implicit Feedback," in Computer, vol. 40, no. , pp. 34-40, 2007.