Brunel University Research Archive (BURA) >
Schools >
School of Information Systems, Computing and Mathematics >
School of Information Systems, Computing and Mathematics Research Papers >

Please use this identifier to cite or link to this item:

Title: Automated user modeling for personalized digital libraries
Authors: Frias-Martinez, E
Magoulas, G
Chen, SY
Macredie, RD
Keywords: Digital libraries
User modeling
Adaptive library services
Publication 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:School of Information Systems, Computing and Mathematics Research Papers
Economics and Finance
Computer Science

Files in This Item:

File Description SizeFormat
chensy.pdf936.17 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.


Library (c) Brunel University.    Powered By: DSpace
Send us your
Feedback. Last Updated: September 14, 2010.
Managed by:
Hassan Bhuiyan