Abstract
Traditional digital library services are built on the explicit needs of the user. The information needs of the user with specific digital resources associated with key words. This is a passive information retrieval service, only to meet the basic needs of users, not through the user’s interest in reading and reading goals to provide targeted services. Through the user log information, we can mine user preferences of different digital resources, to establish a list of user preferences. By the user preference list of association and similarity computation, this paper presents a collaborative filtering algorithm based on user preference list to help readers discover more useful knowledge and information in the mass of digital resources in the digital library system.
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© 2012 Springer-Verlag Berlin Heidelberg
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Feng, G., Zhiyou, L., Huixin, L. (2012). Collaborative Filtering Algorithm Based on the Preference List in the Digital Library. In: Liu, C., Wang, L., Yang, A. (eds) Information Computing and Applications. ICICA 2012. Communications in Computer and Information Science, vol 307. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34038-3_62
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DOI: https://doi.org/10.1007/978-3-642-34038-3_62
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34037-6
Online ISBN: 978-3-642-34038-3
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