A Survey on Improving the Efficiency of Different Web Structure Mining Algorithms
Preeti Chopra1, Md. Ataullah2
1Preeti Chopra, M.Tech,  Department of Computer Science and Engineering. Lovely professional University, Phagwara, Punjab, India.
2Md. Ataullah: Assistant Professor, Lovely professional University, Phagwara, Punjab, India.
Manuscript received on January 25, 2013. | Revised Manuscript received on February 17, 2013. | Manuscript published on February 28, 2013. | PP: 296-298 | Volume-2 Issue-3, February 2013.  | Retrieval Number: C1110022313/2013©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: With the rapid increase in internet technology, users get easily confused in large hyper text structure. Providing the relevant information to user is primary goal of the website owner. In order to achieve this goal, they use the concept of web mining. Web mining is used to categorize users and pages by analyzing the users’ behavior, the content of the pages, and the order of the URLs that tend to be accessed in order [1]. Web structure mining plays very important role in this approach. It’s defined as the process of analyzing the structure of hyperlink using graph theory. There are many proposed algorithms for web structure mining such as Pagerank Algorithm, HITS, Weighted pagerank Algorithm, Topic Sensitive Pagerank Algorithm (TSPR), weighted page content rank Algorithm (WPCR ) etc. In this paper, we have described the outline of all the algorithms and identify their strengths and limitations.
Keywords: HITS, Pagerank algorithm, TSPR, Web mining weighted pagerank algorithm, WPCR etc.