Recommender Systems: An Introduction by Dietmar Jannach, Markus Zanker, Alexander Felfernig, Gerhard Friedrich

Recommender Systems: An Introduction Dietmar Jannach, Markus Zanker, Alexander Felfernig, Gerhard Friedrich ebook
Publisher: Cambridge University Press
ISBN: 0521493366, 9780521493369
Format: pdf
Page: 353

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 book is a very helpful introduction for all researcher that want to conduct research on personalization, learner support and knowledge management through recommender systems. €Which digital camera should I buy? Playlist sequencing talk, Recommenders '06 Photo by davidjennings, cc licensed. Most interesting to me was John Riedl's talk and subsequent discussion about the impact of recommender systems on community. In domains where the items consist of music or video However, collaborative filtering does introduce certain problems of its own: Early rater problem. Recommender systems recommend objects regardless of potential adverse effects of their overcrowding. Both content-based filtering and collaborative filtering have there strengths and weaknesses. What is the best holiday for me and my family? Recommender Systems: An Introduction, 9780521493369 (0521493366), Cambridge University Press, 2010. Three specific problems can be distinguished for content-based filtering: Content description. In some domains generating a useful description of the content can be very difficult.