Name
Abstract | ||
|---|---|---|
Social tagging in online communities has become an important method for reflecting classified thoughts of individual users. A number of social Web sites provide tagging functionalities and also offer folksonomies within or across the sites. However, it is practically not easy to find users' interests based on such folksonomies. In this paper, we provide a novel approach for clustering user-centric interests by analyzing tagging practices of individual users. To do this, we collect Really Simple Syndication data from blogosphere, find conceptual clusters using formal concept analysis, and then evaluate the significance of these clusters. The results of the empirical evaluation show that we can effectively recommend different collections of tags to an individual or a set of users. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/TSMCA.2011.2132709 | IEEE Transactions on Systems, Man, and Cybernetics, Part A |
Keywords | Field | DocType |
classified thought,social tagging,tagging practices,empirical evaluation show,simple syndication data,tagging practice,representing user interests,formal concept analysis,different collection,social web site,individual user,conceptual cluster,data mining,social web,clustering,really simple syndication,conceptual clustering,semantics,ontologies,indexing terms,semantic web,lattices,concept analysis | Ontology (information science),World Wide Web,Social web,Computer science,Semantic Web,Blogosphere,Cluster analysis,Formal concept analysis,RSS,Semantics | Journal |
Volume | Issue | ISSN |
41 | 4 | 1083-4427 |
Citations | PageRank | References |
7 | 0.46 | 21 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hak-Lae Kim | 1 | 67 | 4.90 |
| J. G. Breslin | 2 | 57 | 2.77 |
| Stefan Decker | 3 | 5799 | 643.68 |
| Hong-Gee Kim | 4 | 225 | 22.83 |