Abstract
We propose a multilayered semantic social network model that offers different views of common interests underlying a community of people. The applicability of the proposed model to a collaborative filtering system is empirically studied. Starting from a number of ontology-based user profiles and taking into account their common preferences, we automatically cluster the domain concept space. With the obtained semantic clusters, similarities among individuals are identified at multiple semantic preference layers, and emergent, layered social networks are defined, suitable to be used in collaborative environments and content recommenders.
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Cantador, I., Castells, P. (2006). Multilayered Semantic Social Network Modeling by Ontology-Based User Profiles Clustering: Application to Collaborative Filtering. In: Staab, S., Svátek, V. (eds) Managing Knowledge in a World of Networks. EKAW 2006. Lecture Notes in Computer Science(), vol 4248. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11891451_30
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DOI: https://doi.org/10.1007/11891451_30
Publisher Name: Springer, Berlin, Heidelberg
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