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Recommendation Process in SR1 Web Document Recommender System

Author(s): Dan MUNTEANU

Journal: Annals of Dunarea de Jos
ISSN 1221-454X

Volume: 31;
Issue: 2;
Start page: 22;
Date: 2008;
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Keywords: web document recommender system | content filtering | collaborative filtering | vector space model

This paper presents a recommender system for web documents (given as bookmarks). The system uses for classification a combination of content, event and collaborative filters and for recommendation a modified Pearson-r algorithm. The algorithm for recommendation is using not only the correlation between users but also the similarity between classes. Some experimental results that support this approach are also presented.

Tango Rapperswil
Tango Rapperswil

RPA Switzerland

Robotic Process Automation Switzerland