Optimal Ranking for Video Recommendation
- Cite this paper as:
- Gantner Z., Freudenthaler C., Rendle S., Schmidt-Thieme L. (2010) Optimal Ranking for Video Recommendation. In: Daras P., Ibarra O.M. (eds) User Centric Media. UCMEDIA 2009. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 40. Springer, Berlin, Heidelberg
Item recommendation from implicit feedback is the task of predicting a personalized ranking on a set of items (e.g. movies, products, video clips) from user feedback like clicks or product purchases. We evaluate the performance of a matrix factorization model optimized for the new ranking criterion BPR-Opt on data from a BBC video web application. The experimental results indicate that our approach is superior to state-of-the-art models not directly optimized for personalized ranking.
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