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

Authors:
Jose Javier Astrain
Alberto Cordoba
Francisco Echarte
Jesus Villadangos

Keywords: Social interest discovering, syntactic variations, collaborative tagging systems

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.

Pages: 49 to 54

Copyright: Copyright (c) IARIA, 2010

Publication date: October 25, 2010

Published in: conference

ISSN: 2308-4510

ISBN: 978-1-61208-104-5

Location: Florence, Italy

Dates: from October 25, 2010 to October 30, 2010