Extraction and classification of dense communities in the Web (Rapporti tecnici, manuali, carte geologiche e tematiche e prodotti multimediali)

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  • Extraction and classification of dense communities in the Web (Rapporti tecnici, manuali, carte geologiche e tematiche e prodotti multimediali) (literal)
Anno
  • 2006-01-01T00:00:00+01:00 (literal)
Alternative label
  • Dourisboure Y., Geraci F., Pellegrini M. (2006)
    Extraction and classification of dense communities in the Web
    (literal)
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  • Dourisboure Y., Geraci F., Pellegrini M. (literal)
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  • http://dienst.isti.cnr.it/Dienst/UI/2.0/Describe/ercim.cnr.iit/2006-TR-09?tiposearch=ercim&langver= (literal)
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  • Rapporti tecnici - IIT 2006-TR-09 (literal)
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  • Abstract: The World Wide Web (WWW) is rapidly becoming important for society as a medium for sharing data, information and services, and there is a growing interest in tools for understanding collective behaviors and emerging phenomena in the WWW. In this paper we focus on the problem of searching and classifying communities in the web. Loosely speaking a community is a group of pages related to a common interest. More formally communities have been associated in the computer science literature with the existence of a locally dense sub-graph of the web-graph (where web pages are nodes and hyper-links are arcs of the web-graph) The core of our contribution is a new scalable algorithm for finding relatively dense subgraphs in massive graphs. We apply our algorithm on web-graphs built on three publicly available large crawls of the web (with raw sizes up to 120M nodes and 1G arcs). The effectiveness of our algorithm in finding dense subgraphs is demonstrated experimentally by embedding artificial communities in the web-graph and counting how many of these are blindly found. Effectiveness increases with the size and density of the communities: it is close to 100% for dense communities of a hundred nodes or more. Moreover it is still about 80% even for small communities of twenty nodes and density at 50% of the arcs present. (literal)
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  • Extraction and classification of dense communities in the Web (literal)
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