Fraunhofer Institut für Integrierte Publikations-und Informationssysteme IPSI

Filters

2
2
2
Reset filters

Settings
Now showing 1 - 2 of 2
  • Publication
    Exploiting lexical knowledge in learning user profiles for intelligent information access to digital collections
    ( 2005)
    Semeraro, G.
    ;
    Lops, P.
    ;
    Degemmis, M.
    ;
    Niederée, C.
    ;
    Stewart, A.
    Algorithms designed to support users in retrieving relevant information base their relevance computations on user profiles, in which representations of the users interests are maintained. This paper focuses on the use of supervised machine learning techniques to induce user profiles for Intelligent Information Access. The access must be personalized by profiles allowing users to retrieve information on the basis of conceptual content. To address this issue, we propose a method to learn sense-based user profiles based on WordNet, a lexical database.
  • Publication
    Ontologically-enriched unified user modeling for cross-system personalization
    ( 2005)
    Mehta, B.
    ;
    Niederée, C.
    ;
    Stewart, A.
    ;
    Degemmis, M.
    ;
    Lops, P.
    ;
    Semeraro, G.
    Personalization today has wide spread use on many Web sites. Systems and applications store preferences and information about users in order to provide personalized access. However, these systems store user profiles in proprietary formats. Although some of these systems store similar information about the user., exchange or reuse of information is not possible and information is duplicated. Additionally, since user profiles tend to be deeply buried inside such systems, users have little control over them. This paper proposes the use of a common ontology-based user context model as a basis for the exchange of user profiles between multiple systems and, thus, as a foundation for cross-system personalization.