Efficient calculation of PageRank using TrustRank and Anti-TrustRank
- Jignesh Patel
- Swati Patel
- Hiteishi Diwanji
Web Structure Mining, Web Content Mining, TrustRank, Anti-TrustRank, Spam Page, PageRank
Web is collection of millions of pages and Web is growing and changing very rapidly, millions of pages are added and deleted every day in web. The information present on the World Wide Web is of great need, the world is full of questions and the web is the major source of gaining information about user’s specific query. As per the web search engine for the query, a millions of pages are retrieved among which the quality of the pages that are retrieved is questioned. Numbers of mathematical algorithms are used for the efficient ranking purpose. In this paper we have explained algorithm which uses content for calculating PageRank called web content mining. In this paper we are trying to reduce the problem of theme drift. For that we have added new parameters TrustRank and Anti-TrustRank. These parameters are used to calculate relevancy and irrelevancy of the page to user query. In our proposed work we use web content mining for calculating the PageRank values of the pages. Anti-TrustRank is measurement of antitrust of page. TrustRank is measurement of trust of page.
Jignesh Patel, Swati Patel, Hiteishi Diwanji. "Efficient calculation of PageRank using TrustRank and Anti-TrustRank".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.2, Issue 2, pp.1895-1898, URL :https://rjwave.org/ijedr/papers/IJEDR1402098.pdf
Volume 2 Issue 2
Pages. 1895-1898
