Research And Application Of Web Community Discovery Based On Hyperlink Analysis

With the rapid growth of web information, it becomes more and more important and challenging research problem that how to retrieve latent and useful information among the gigantic amount of Web information, and utilize web information adequately and effectively on information domain. It is very valuable to search web community discovery in practice and academic study, web community is very important web information, it can partition web information valuably, it reflects prevalent and complicated clustering relation and hierarchical relation on web.Most abundant information clue has been provided for web community discovery researching in the relation of web page links, web community discovery was based on hyperlink analysis technology. We can gain useful topological relation from web page links structure, we can analyze corresponding functional and semantic meaning further, and filtrate useless information. It will be redound to enhance web information retrieval performance and precision that web community discovery algorithm is used to search engine, and can implement web information clustering in some ways.Based on the analysis of current web and its data character, the modeling methods of web topological structure, web topological structure model, web information retrieval model and the architecture of search engine, the classical web community discovery algorithm was researched on the basis of web hyperlink analysis technology in this paper, and its improved algorithm was proposed. and web community discovery application system was constructed based on current search software and tool package. the intuitionistic method that how to clustering partition web information set by web community discovery algorithm was discussed, as is very valuable in practice and academic study to improve retrieval results of search engine.