2015 10th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)
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Abstract

Identifying similar items to the ones provided as input to a search system, is a challenging task. The main issues concern not only the management of large collections of data, but also the profiling of the users, who usually have different opinions, tastes and expertise. In this paper we propose a preliminary investigation about the improvements in the accuracy of a search system provided by network analysis techniques supporting the discovery of relations among the items stored in the repository. For this reason, we have developed the SEEN prototype, a keyword search tool exploiting network analysis. SEEN has been evaluated against a relational version of the DBLP repository. The results of the preliminary experiments show that the the information provided by networks can improve the effectiveness of the results.
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