Web Page Ranking Algorithms Through Centrality Measures
DOI:
https://doi.org/10.26713/jims.v9i3.758Keywords:
In-degree, Out-degree, Eigen centrality, Page rankAbstract
In this paper we give a brief overview of the adjacency matrix based page rank that we used in the Google search engine. In this paper various centrality measures discussed like in-degree centrality, out-degree centrality, degree centrality and Eigen centrality. We have applied the above mentioned centrality measures to web page ranking. This approach does not involve any iterative technique. This centrality measures are better than original iterative based page rank algorithm for ranking the web pages.Downloads
References
K. Bharat and A. Broder, A technique for measuring the relative size and overlap of public web search engines, Computer Networks and ISDN Systems 30 (1) (1998), 379 – 388.
T. Bhatia, Link Analysis Algorithms for web mining, International Journal of Computer Application 2 (1) (2011) 243 – 246.
M. Bianchini, M. Gori and F. Scarselli, Inside page rank, ACM Transactions on Internet Technology 5 (1) (2005), 92 – 128.
S. Brin and C. Page, The anatomy of a large scale hypertentud web search engine, Computer Network and ISDN Systems 30 (1-7) (1998), 107 – 117.
S. Chakrabarti, B. Dom, D. Gibson, J. Kleinberg, R. Kumar, P. Raghavan, S. Rajagopalan and Tomkins, Mining the link structure of world wide web, IEEE Computer 32 (1999), 60 – 67.
L. Choudhary and B. Shankar, Burdark role of ranking algorithms for information retrieval, International Journal of Artificial Intelligence and Application 3 (4) (2012), 21 – 34.
C.H.Q. Ding, X. He, P. Husbands, H. Zha and H.D. Simon, Page rank: HITS and a unified framework for link Analysis, in Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development on Information Retrieval, Tampere, Finland, pp. 353 – 354.
http://googleblog.blogspot.com/2008.
B. Jaganathan and K. Desikan, Category-based pagerank algorithm, International Journal of Pure and Applied Mathematics 101 (5) (2015), 811 – 820.
B. Jaganathan and K. Desikan, Hermition matrix based pagerank algorithm, Global Journal of Pure and Applied Mathematics, 12 (1-3) (2016), 271 – 280.
B. Jaganathan and K. Desikan, Penalty-based pagerank algorithm, ARPN Journal of Engineering and Applied Sciences 10 (5) (2015), 2000 – 2003.
B. Jaganathan and K. Desikan, Weighted pagerank algorithm based on in-out weight of webpages, Indian Journal of Science and Technology 8 (34) (2015), 1 – 6.
J.M. Klienberg, Authoritative sources in a hyperlinked environment, Journal of the ACM 46 (5) (1999), 604 – 632.
A.N. Langville and C.D. Meyer, Google Page Rank and Beyond: The Science of Search Engine Rankings, Princeton University Press, Princeton, New Jersey (2006).
L. Page, S. Brin, R. Motwani and T. Winograd, The Page Rank Citation Ranking: Bringing Order to the Web, Stanford Digital Library Technologies Project (1998).
P. Ravikumar and A.K. Singh, Web structure mining exploring hyperlinks and algorithms for information retrieval, American Journal of Applied Sciences 7 (6) (2010), 840 – 845.
D. Sepandar, H.K. Taher, H. Christopher, D.M. Gene and H. Golub, Exploiting the Block Structure of the Web for Computing Page Rank, Stanford University Technical Report (2003).
D.K. Sharma and A.K. Sharma, A comparative analysis of web page ranking algorithms, Journal on Computer Science and Engineering 2 (8) (2010), 2670 – 2676.
J. Wang, Z. Chen, L. Tao, W. Ma and W. Liu, Ranking user's relevance to a topic through link analysis on web logs, WISM (2002), pp. 49 – 54, dl.ac.org.
Downloads
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a CCAL that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.