Abstract
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.
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Neumann, A.W. (2007). Motivating and Supporting User Interaction with Recommender Systems. In: Kovács, L., Fuhr, N., Meghini, C. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2007. Lecture Notes in Computer Science, vol 4675. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74851-9_36
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DOI: https://doi.org/10.1007/978-3-540-74851-9_36
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