Automated user modeling for personalized digital libraries

Frias-Martinez, E. and Magoulas, George and Chen, S.Y. and Macredie, R.D. (2006) Automated user modeling for personalized digital libraries. International Journal of Information Management 26 (3), pp. 234-248. ISSN 0268-4012.

Full text not available from this repository.

Official URL: https://doi.org/10.1016/j.ijinfomgt.2006.02.006

Abstract

Digital libraries (DLs) 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 DLs. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in DLs 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 DLs that satisfy a user's necessity for information: Adaptive DLs, libraries that automatically learn user preferences and goals and personalize their interaction using this information.

Metadata

Item Type:	Article
School:	Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences
Depositing User:	Sarah Hall
Date Deposited:	22 Jun 2021 12:47
Last Modified:	09 Aug 2023 12:51
URI:	https://eprints.bbk.ac.uk/id/eprint/44835

Statistics

Archive Staff Only (login required)

Edit/View Item