Content filtering research based on web community structure
The web contents are massive, diverse and semantics-missing, which bring significant challenges to the content-filtering. This paper proposes a new method of web content-filtering, which takes full advantage of the web structure feature that the similar topic webpages integrate into the web community, and uses the web community detection algorithm to get more content-similar webpages after filtering one webpage. In addition, by constructing and analyzing the associated mathematical model, it proves that this method significantly raised the efficiency, compared with the other third-party content-filtering technology.