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 proposed 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. © 2006 International Federation for Information Processing.
CITATION STYLE
Godoy, D., & Amandi, A. (2006). Learning browsing patterns for context-aware recommendation. IFIP International Federation for Information Processing, 217, 61–70. https://doi.org/10.1007/978-0-387-34747-9_7
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