International Journal of E-Business Development          
International Journal of E-Business Development(IJED)
ISSN:2225-7411(Print)      ISSN:2226-7336(Online)
Editor-in-chief: Prof. Steven Li, RMIT University, Australia
Website: www.academicpub.org/ijed/
A Clustering Approach for Tag Recommendation in Social Environments
Full Paper(PDF, 752KB)
Abstract:
Collaborative tagging is the process by which users classify shared content using keywords. Although its popularity keeps growing on the Web, content retrieval can be difficult since people tag differently. Moreover, there are some well-known linguistic phenomena. Recently, several attempts to avoid such limitations by recommending tags to users or by creating tag clusters have been presented. In this paper we propose an approach to cluster tags by monitoring the activity of the users in a tagging system. The created clusters can be used to recommend tags when a user uploads or searches a resource, in order to facilitate content retrieval. Experiments are performed by comparing with a classic tag clustering approach and results show the capability of the approach to cluster strongly related tags.
Keywords:Tag Clustering; Social Recommendation; Tagging System
Author: Ludovico Boratto1, Salvatore Carta1, Matteo Manca1, Fabrizio Mulas1, Paolo Pilloni1, G. Michele Pinna1, Eloisa Vargiu2
1.Dipartimento di Matematica e Informatica, Università di Cagliari Via Ospedale, 72 – 09124 Cagliari, Italy
2.Barcelona Digital (bDigital) C/ Roc Boronat, 117 - 08018 Barcelona, Spain
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