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Title: Automated user modeling for personalized digital libraries
Authors: Frias-Martinez, E
Magoulas, G
Chen, SY
Macredie, RD
Keywords: Digital libraries;User modeling;Personalization;Adaptive library services
Issue Date: 2006
Publisher: Elsevier
Citation: International Journal of Information Management, 26(3): 234-248, Jun 2006
Abstract: Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user’s necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information.
Appears in Collections:Economics and Finance
Computer Science
Dept of Computer Science Research Papers

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