A Graph-Based Clustering Scheme for Identifying Related Tags in Folksonomies View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2010

AUTHORS

Symeon Papadopoulos , Yiannis Kompatsiaris , Athena Vakali

ABSTRACT

The paper presents a novel scheme for graph-based clustering with the goal of identifying groups of related tags in folksonomies. The proposed scheme searches for core sets, i.e. groups of nodes that are densely connected to each other by efficiently exploring the two-dimensional core parameter space, and successively expands the identified cores by maximizing a local subgraph quality measure. We evaluate this scheme on three real-world tag networks by assessing the relatedness of same-cluster tags and by using tag clusters for tag recommendation. In addition, we compare our results to the ones derived from a baseline graph-based clustering method and from a popular modularity maximization clustering method. More... »

PAGES

65-76

References to SciGraph publications

  • 2005. Ontologies Are Us: A Unified Model of Social Networks and Semantics in THE SEMANTIC WEB – ISWC 2005
  • 2008. Personalizing Navigation in Folksonomies Using Hierarchical Tag Clustering in DATA WAREHOUSING AND KNOWLEDGE DISCOVERY
  • 2006. Information Retrieval in Folksonomies: Search and Ranking in THE SEMANTIC WEB: RESEARCH AND APPLICATIONS
  • Book

    TITLE

    Data Warehousing and Knowledge Discovery

    ISBN

    978-3-642-15104-0
    978-3-642-15105-7

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-15105-7_6

    DOI

    http://dx.doi.org/10.1007/978-3-642-15105-7_6

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1019664126


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