| Titolo | Learning preferences of users accessing digital libraries |
|---|---|
| Tipo di pubblicazione | Monografia |
| Anno di Pubblicazione | 2003 |
| Autori | Licchelli, O., Lops P., Semeraro G., Bordoni L., and Poggi F. |
| Series Title | Proceedings of the 10th ISPE International Conference on Concurrent Engineering |
| Number of Pages | 457-465 |
| Parole chiave | Algorithms, 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. |
| URL | https://www.scopus.com/inward/record.uri?eid=2-s2.0-1442285341&partnerID=40&md5=ec906a64439f5e85e38a004acad48089 |
| Citation Key | Licchelli2003457 |
