TagRank: A New Rank Algorithm for Webpage Based on Social Web

摘要

Due to the problem that webpage on web2.0 can't be ranked effectively at present, we analyze and utilize the time factor of the new data source tag and propose a new algorithm named TagRank based on social annotations for page ranking. This algorithm digs the annotation behavior of the web users, calculates the "heat" of the tags, consequently, it can response the true quality of tags more externally and improve the veracity of page ranking. The experiment shows that our algorithm works effectively.