Abstract. Under Social Tagging Systems, a typical Web 2.0 application, users label digital data sources by using freely chosen textual descriptions (tags). Mining tag information reveals the topic-domain of users interests and significantly contributes in a profile construction process. In this paper we propose a clustering framework which groups users according to their preferred topics and the time locality of their tagging activity. Experimental results demonstrate the efficiency of the proposed approach which results in more enriched time-aware users profiles.
For instance, Koutsonikola et al. REF proposes a clustering framework which groups users according to their preferred topics and the time locality of their tagging activity.
Clustering of Social Tagging System Users: A Topic and Time Based Approach
WISE
Computer Science