Título: Learning browsing patterns for context-aware recommendation
Autores: Godoy, Daniela Lis
Amandi, Analía
Fecha: 2012-11-08
2006-08
2006-08
Publicador: Unversidad Nacional de La Plata
Fuente:

Tipo: Objeto de conferencia
Objeto de conferencia
Tema: Patterns
Information browsers
Ciencias Informáticas
Descripción: The success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both user interests and browsing patterns. The pro- posed approach analyzes the browsing behavior of users to derive a semantically enhanced context that points out the information which is likely to be relevant for a user according to its current activities.
IFIP International Conference on Artificial Intelligence in Theory and Practice - Agents 1
Idioma: Inglés