<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Symeon Papadopoulos</style></author><author><style face="normal" font="default" size="100%">Yiannis Kompatsiaris</style></author><author><style face="normal" font="default" size="100%">Athena Vakali</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A graph-based clustering scheme for identifying related tags in folksonomies</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the 12th international conference on Data warehousing and knowledge discovery</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">DaWaK’10</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">community detection</style></keyword><keyword><style  face="normal" font="default" size="100%">folksonomies</style></keyword><keyword><style  face="normal" font="default" size="100%">graph-based clustering</style></keyword><keyword><style  face="normal" font="default" size="100%">tag recommendation</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2010</style></year></dates><publisher><style face="normal" font="default" size="100%">Springer-Verlag</style></publisher><pub-location><style face="normal" font="default" size="100%">Berlin, Heidelberg</style></pub-location><pages><style face="normal" font="default" size="100%">65–76</style></pages><isbn><style face="normal" font="default" size="100%">3-642-15104-3, 978-3-642-15104-0</style></isbn><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The paper presents a novel scheme for graph-based clusteringwith the goal of identifying groups of related tags in folksonomies.The proposed scheme searches for core sets, i.e. groups of nodes thatare densely connected to each other by efficiently exploring the twodimensional 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.&lt;/p&gt;
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