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.
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Papadopoulos, S., Kompatsiaris, Y., Vakali, A. (2010). A Graph-Based Clustering Scheme for Identifying Related Tags in Folksonomies. In: Bach Pedersen, T., Mohania, M.K., Tjoa, A.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2010. Lecture Notes in Computer Science, vol 6263. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15105-7_6
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DOI: https://doi.org/10.1007/978-3-642-15105-7_6
Publisher Name: Springer, Berlin, Heidelberg
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