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Recommender Systems: An Introduction Dietmar Jannach, Markus Zanker, Alexander Felfernig, Gerhard Friedrich
Publisher: Cambridge University Press

As for the former perhaps the following would be more useful: http://paloalto.thlab.net/publications/80. Playlist sequencing talk, Recommenders '06 Photo by davidjennings, cc licensed. ň�发现另一本介绍推荐系统的好书Recommender Systems:An Introduction （第一本是Recommender system handbook），找了很久才找到地址，给大家分享一下（下载地址在文章末尾）。 本书的目录如下：. Related Work (Recommender Systems Taxonomies). 1- A moderator decides on what products to sell in the package, 2- You build a smart recommendation system that can do this job for the moderator. The Author introduced 5 papers, which offered different taxonomies. For these two options, smart mechanisms like the ones used for personalization are Thanks to this, products that are normally not advertised because of their unpopularity are introduced to buyers that might buy those products. Most interesting to me was John Riedl's talk and subsequent discussion about the impact of recommender systems on community. This informative (and interesting) talk introduced some of the concepts involved in developing personalisation algorithms for the grocery retail sector, and discussed wider aspects such as the business challenges that have or are likely to be addressed. This webinar provides an introduction to recommender systems, describing the different types of recommendation technologies available and how they are used in different applications today. Recommendation systems: privacy and interactivity. Please note that only positive recommendations can be left. The paper you link deals strictly with the latter. Video of UCB Data Mining Lecture on Collaborative filtering and Recommender Systems Here is Apr 13, 2011 Lecture in UC. Feb 9, Data Mining Lecture, Naive Bayes. I spent Tuesday and Wednesday last week at a 'summer school' on recommender systems, hosted by MyStrands in Bilbao (thanks, sincerely, to them for their hospitality, and less sincerely to I recommend Juntae Kim's presentation as an introduction. The talk As part of this collaboration, an on-line personalised retail recommender systems was developed, which also serve as a test-bed to evaluate the performance of their personalisation algorithms. Feb 2, Data Mining Lecture, Introduction, R, Logistic Regression. We have also introduced a recommendation rating system where customers can recommend TPs for the benefit of other customers.