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Learning preferences of users accessing digital libraries

TitoloLearning preferences of users accessing digital libraries
Tipo di pubblicazioneMonografia
Anno di Pubblicazione2003
AutoriLicchelli, O., Lops P., Semeraro G., Bordoni L., and Poggi F.
Series TitleProceedings of the 10th ISPE International Conference on Concurrent Engineering
Number of Pages457-465
Parole chiaveAlgorithms, Clustering algorithms, Computer architecture, Data reduction, Database systems, Digital libraries, Information dissemination, Information sources, Learning systems, Network protocols, Project management, Societies and institutions, Virtual reality, World Wide Web, XML
Abstract

The World Wide Web is a huge information source for Digital Libraries, but it has a significant problem: the information overload. Therefore, the main challenge is to support users to locate the right information at the right time. In this paper we present the Profile Extractor, a personalization component, based on Machine Learning techniques, which allows for the discovery of preferences, needs and interests of users accessing to COVAX (Contemporary Culture Virtual Archives in XML) digital library. Moreover, we examined how user profiles can be exploited in the Covax digital library to improve the retrieval process.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-1442285341&partnerID=40&md5=ec906a64439f5e85e38a004acad48089
Citation KeyLicchelli2003457