2016 IEEE 32nd International Conference on Data Engineering (ICDE) (2016)
May 16, 2016 to May 20, 2016
Royi Ronen , Microsoft Israel
Elad Yom-Tov , Microsoft Research Israel
Gal Lavee , Microsoft Israel
Collaborative filtering (CF) recommendation systems are one of the most popular and successful methods for recommending products to people. CF systems work by finding similarities between different people according to their past purchases, and using these similarities to suggest possible items of interest. In this work we show that CF systems can be enhanced using Internet browsing data and search engine query logs, both of which represent a rich profile of individuals' interests.
Internet, Search engines, Collaboration, History, Measurement, Filtering, Motion pictures
R. Ronen, E. Yom-Tov and G. Lavee, "Recommendations meet web browsing: enhancing collaborative filtering using internet browsing logs," 2016 IEEE 32nd International Conference on Data Engineering (ICDE), Helsinki, Finland, 2016, pp. 1230-1238.