An Algorithm for the Improvement of Tag-based Social Interest Discovery – SEMAPRO 2010

Abstract

The success of Web 2.0 has generated many interesting and challenging problems as the discovering of social interests shared by groups of users. The main problem consists on discovering and representing the interest of the users. In this paper, we propose a fuzzy based algorithm that improves the Internet Social Interest Discovery algorithm. This algorithm discovers the common user interests and clusters users and their saved resources by different interest topics. The collaborative nature of social network systems and their flexibility for tagging, produce frequently multiple variations of a same tag. We group syntactic variations of tags using a similarity measure improving the quality of the results provided by the Internet Social Interest Discovery algorithm.

Authors

José Javier Astrain, Alberto Córdoba, Francisco Echarte, Jesús Villadangos

Reference

Astrain, J.J., Córdoba, A., Echarte, F. y Villadangos, J. (2010). An Algorithm for the Improvement of Tag-based Social Interest Discovery. En SEMAPRO’10: Proceedings of The Fourth International Conference on Advances in Semantic Processing, pages 49—54, Florencia, Italia.