Improvement of PageRank for Focused Crawler

The rapid growth of the World-Wide Web poses unprecedented scaling challenges for general-purpose crawlers. Focused crawler is developed to collect relevant web pages of interested topics form the Internet. The PageRank algorithm is used in ranking web pages. It estimates the page \´s authority by taking into account the link structure of the Web. However, it assigns each outlink the same weight and is independent of topics, resulting in topic-drift. In this paper, we proposed an improved PageRank algorithm, which we called "T- PageRank", and it based on "topical random surfer". The experiment in focused crawler using the T-PageRank has better performance than the Breath-first and PageRank algorithms.