Doina Alexandra Dumitrescu
ABSTRACT
Novelty detection algorithms usually employ similarity measures with the previous seen and relevant documents to decide if a document is of user's interest. The problem that arises by using this approach is that the system might recommend redundant documents. Thus, it has become extremely important to be able to distinguish between "redundant" and "novel" information. To address this limitation, we apply a contextual and semantic approach by building the user profile using self-organizing maps that have the advantage to easily follow the changes in the users interests.
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Index Terms
- Using Context to Get Novel Recommendation in Internet Message Streams
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