J4 ›› 2012, Vol. 39 ›› Issue (3): 196-201.doi: 10.3969/j.issn.1001-2400.2012.03.032

• Original Articles • Previous Articles     Next Articles

Topological graph based tag semantic relatedness measure for social tagging systems

ZHANG Changli1;HOU Ronghui2   

  1. (1. School of Information Engineering, Chang'an Univ., Xi’an  710064, China;
    2. School of Telecommunication Engineering, Xidian Univ., Xi'an  710071, China)
  • Received:2011-10-14 Online:2012-06-20 Published:2012-07-03
  • Contact: ZHANG Changli E-mail:clzhang@chd.edu.cn

Abstract:

Regarding the problems of the structureless organization and implicit meaning of tags in the social tagging systems in Web2.0, a topological graph based formal model of semantic relatedness measure is proposed to fully exploit the interplay of the semantic co-relations among a large number of tags. In this model, the results of the statistics based tag relatedness measures are used to extend the topological graph of tags co-occurrence network with weights of edges, two operators are invented to synthetically compute the overall effect of the weights within the extended graph, so that the interplay of semantic co-relations of tags can be explicitly represented and the semantic relatedness of tags can also be measured soundly. To illustrate the calculating process and to testify the validness and feasibility of the calculating results for this model, an experiment is conducted with the set of the most popular tags crawled from Flickr.com, a famous photos sharing website. Experimental results show that the model can lead to better results, and is highly applicable to the guidance and constraint of annotating behaviors in Web2.0 environments.

Key words: semantic relatedness, social tagging system, tags co-occurrence network, topological graph, Web2.0

CLC Number: 

  • TP393.07