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A New Ranking Algorithm for Search Engine: Content’s Weight based Page Ranking

by Charanjit Singh, Vijay Laxmi, Arvinder Singh Kang
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 152 - Number 7
Year of Publication: 2016
Authors: Charanjit Singh, Vijay Laxmi, Arvinder Singh Kang
10.5120/ijca2016911895

Charanjit Singh, Vijay Laxmi, Arvinder Singh Kang . A New Ranking Algorithm for Search Engine: Content’s Weight based Page Ranking. International Journal of Computer Applications. 152, 7 ( Oct 2016), 26-28. DOI=10.5120/ijca2016911895

@article{ 10.5120/ijca2016911895,
author = { Charanjit Singh, Vijay Laxmi, Arvinder Singh Kang },
title = { A New Ranking Algorithm for Search Engine: Content’s Weight based Page Ranking },
journal = { International Journal of Computer Applications },
issue_date = { Oct 2016 },
volume = { 152 },
number = { 7 },
month = { Oct },
year = { 2016 },
issn = { 0975-8887 },
pages = { 26-28 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume152/number7/26333-2016911895/ },
doi = { 10.5120/ijca2016911895 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:57:34.183934+05:30
%A Charanjit Singh
%A Vijay Laxmi
%A Arvinder Singh Kang
%T A New Ranking Algorithm for Search Engine: Content’s Weight based Page Ranking
%J International Journal of Computer Applications
%@ 0975-8887
%V 152
%N 7
%P 26-28
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The objective of this paper is to propose a new ranking technique or algorithm for web page rank. Different search engines use various ranking algorithms for the ranking of the web pages. Web Page ranking algorithm works only on the web page repository or indexed pages to the search engine for ranking. In reality, search engines work in two phases one is crawling phase and another is ranking phase. This proposed Algorithm is based on the ranking phase. In this Paper purposed a new ranking algorithm which will be known as Content’s Weight Based Page Ranking Algorithm (CWPRA). This algorithm Calculate the Page Rank based upon the weight of contents which is related to user query. Hope this algorithm provide the best, accurate and sufficient data or information or matter to the user according to the need.

References
  1. S.S. Dhenakaran and K. Thirugnana Sambanthan “web crawler - an overview “International Journal of Computer Science and Communication Vol. 2, No. 1, January-June 2011, pp. 265-267.
  2. Linda Fortney Montgomery College Rockville Campus Library “Web search engines” la 634 aug. 2003.
  3. Singh, C., Laxmi, V. and Singh, A. “Evolution of web Mining” National Conference of Science and Technology (NCAST-2016) at RIMT-IET, MandiGobindgarh, March 2016.
  4. . Singh, Parbhat Kumar., Agarwal, G. and Gupta, S. “A New Ranking Technique for Ranking Phase of Search Engine: Size based Ranking Algorithm (SBRA)”, International Journal of Computer Applications (0975 – 8887), Vol-85-No -5, Nov-2013.
  5. . Pau Valles Fradera, “Personalizing web search and crawling from clickstream data”19/01/2009.
  6. . Massimo Marchiori. “The quest for correct information on the web: Hyper search engines.”, In Proceedings of the Sixth International World Wide Web Conference (WWW6), 1997.
  7. J. Kleinberg. Authoritative sources in a hyperlinked environment. In 9th ACM-SIAM Symposium on Discrete Algorithms, 1998.
  8. Singh, C. and Kautish, S. “Page Ranking Algorithms for Web Mining: A Review” International Journal of Computer Applications (0975 – 8887), International Conference on Advancements in Engineering and Technology (ICAET 2015).
  9. Serge Abiteboul, Mihai Preda, and Gregory Cobena. “Adaptive on-line page importance computation”, In WWW '03: Proceedings of the 12th international conference on WorldWide Web, pages 280-290, New York, NY, USA, 2003. ACM.
Index Terms

Computer Science
Information Sciences

Keywords

Web Mining Search Engine Page Ranking

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