Communications of the ACM
Recommender systems in e-commerce
Proceedings of the 1st ACM conference on Electronic commerce
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Knowledge and Data Engineering
A market-based approach to recommender systems
ACM Transactions on Information Systems (TOIS)
RecoDiver: Browsing behavior-based recommendations on dynamic graphs
AI Communications - Recommender Systems
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This contribution reports on the introduction of explicit recommender systems at the University Library of Karlsruhe. In March 2006, a rating service and a review service were added to the already existing behavior-based recommender system. Logged-in users can write reviews and rate all library documents (books, journals, multimedia, etc.); reading reviews and inspecting ratings are open to the general public. A role system is implemented that supports the submission of different reviews for the same document from one user to different user groups (students, scientists, etc.). Mechanism design problems like bias and free riding are discussed, to address these problems the introduction of incentive systems is described. Usage statistics are given and the question, which recommender system supports which user needs best, is covered. Summing up, recommender systems are a way to combine the support of library user interaction with information access beyond catalog searches.