<?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></contributors><titles><title><style face="normal" font="default" size="100%">GRANULAR GRAPH CLUSTERING IN THE WEB</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2007</style></year></dates><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We investigate the partition of a weighted graph, representing traffic, to a number ofsubgraphs such that both inter(external)-subgraph traffic is minimized and intra(internal)-subgraph traffic is maximized. The long-term objective is Web-navigation support. Wepursue a solution by applying a simple agglomerative clustering algorithm, or ACA forshort, to a metric space emerging from a weighted graph. An enabling technology isinspired from mathematical lattice theory. The proposed techniques compare favorablywith other techniques in an application to a graph stemming from a University Web-site.&lt;/p&gt;
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