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

Nudging Serendipity – Guiding users toward discovery of unknown unknowns. We introduced recommender systems and compared them to relevant work in TEL like adaptive educational hypermedia, learning networks, educational data mining and learning analytics. Recommender systems are fast becoming as standard a tool as search engines, helping users to discover content that interests them with very little effort. Manning, C.D., Raghavan, P., Schtze, H.: Introduction to Information Retrieval. Howdy, since the introduction of collecting ecommerce data (logging of purchased products) it would be great, to build something like product recommendations via the API. Following the post on evaluation metrics in your blog, we would be glad to help you testing new evaluation metrics for GraphChi. 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：. The authors then introduced a number of "item re-ranking methods that can generate substantially more diverse recommendations across all users while maintaining comparable levels of recommendation accuracy. Introduction: For this blog assignment, I summarized an interesting academic paper I found using Google Scholar. Until recently, this literature suggests, research on recommendation systems has focused almost exclusively on accuracy, which led to systems that were likely to recommend only popular items, and hence suffered from a "popularity bias'' (Celma and Herrera 2008). The main thrust of the talk had to do with the advantage gained by using multiple behaviors as the source of input data for building a recommendation engine. A model of a trust-based recommendation system on a social network. Introduction to Product Recommendation Engines The hybrid recommender system provides the best of the two aforementioned strategies, which many consider make it the best out the three approaches. Not long ago (this year, actually), with Sherry we wrote a book Chapter on recommender systems focusing on sources of knowledge and evaluation metrics. 9:30 Introductions – all participants introduce themselves. In section 7.4 we explain MAP: Mean Average Precision. This is my first post here and I´ll let my introduction for a later post, but I´d like to share a very scary cool video that explains a bit of what I may be very promising for the recommender systems and vision. Original：http://alban.galland.free.fr/Documents/Enseignements/INF396/recommendersystems-slides.pdf Recommender Systems Alban Galland INRIA-Saclay 18 March 2010 A.