Survey papers which has already been published in journals and slides which were used in invited talks are uploaded here.
- Offline Evaluation for Recommender Systems, Journal of the Japanese Society for Artificial Intelligence, Vol. 29, No. 6, pp. 658-689, 2014. (English slide version). [PDF]
This covers most of the existing evaluation metrics for recommender systems. Actually it covers not only evaluation metrics related to recommendation correctness like precision, recall and F-measure but also those related to users’ discovery like novelty, serendipity and diversity. I recommend this article not only for recommender systems researcher but also for researchers on information retrieval, pattern recognition and machine learning.