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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Cantador, I., & Castells, P. (2006). Multilayered semantic social network modeling by ontology-based user profiles clustering: Application to collaborative filtering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4248 LNAI, pp. 334–349). Springer Verlag. https://doi.org/10.1007/11891451_30
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