Web graph clustering to find Communities on the Web (web Communities )

Search Pointers form the main part of the application on Internet. However, because of Information management hardware, high volume data and word similarity in different fields the most answers to the user's questions aren`t correct. So The web graph clustering and cluster placement in corresponding answers help user to achieve his or her intended results. Also, using clustering methods in the Web community (web communities) can be used to generate automated directory services. In this research the act of clustering has been done by finding the complete bipartite under- graphs . The under- graphs form the core of a community or clustering and by extending the core we can attain to the whole clustering .The whole set of graphs in England are 18 million pages and 300 million links.

web clustering ,community,graph,fuzzy.