An Algorithm for Ranking Web Pages Based on Links and Ant Colony Algorithm

Authors

  • Asma Khonji Department of Computer , Kish International Branch, Islamic Azad University, Kish Island
  • Dr. Ali Harounabadi Professor at Islamic Azad University Kish International

Keywords:

PageRank algorithm, ant colony algorithm, structure-based web mining.

Abstract

With the exponential web growth, techniques of recommender systems and pages ranking algorithms have gained importance over time. Web mining which is considered as a subset of data mining, is being emphasized in three categories: web mining based on application, web mining based on content and web mining based on structure. Pages ranking algorithms operates mainly based on structure-based web mining. In the current study it has been tried to maximize accuracy of pages ranking with combining function and structure-based techniques. Improvement of Page Rank algorithm is performed using user profiles and important attributes to page ranking algorithm (number of inbound and outbound links to pages). Due to the problem broadness, the use of meta-heuristic algorithms (such as ant colony algorithm) has been highlighted in the current study and the fitness function is set so that the increase of iterations will increase the accuracy of PageRank algorithms. The results of the study explain accuracy of the proposed method compared to other methods.

References

Sara Setayesh , Ali Harounabadi, Amir Masoud Rahmani, 2014, Presentation of an Extended Version of the PageRank Algorithm to Rank Web Pages Inspired by Ant Colony Algorithm, International Journal of Computer Applications (0975 – 8887) Volume 85 – No 17

. [2] Brin, S., Page, L. , 1998. The anatomy of a large-scale hypertextual web search engine, Proceedings of the 7th International World Wide Web Conference. Briabane, Australia, Apr 14-18, pp.107-117.

Xing, W., Ghorbani, A. 2004. Weighted PageRank Algorithm. Proceedings of the Second Annual Conference on Communication Networks and Services Research (CNSR’04), IEEE, pp. 305- 314.

Tyagi, N., Sharma, S. 2012. Weighted PageRank Algorithm Based on Number of Visits of Links of Web Page. International Journal of Soft Computing and Engineering (IJSCE), vol.2, pp. 441- 446.

Dinkar, S.K., Kumar, H. 2012. Interaction Information Retrieval and Improved Page Rank Algorithm Based on Aceess Duration of Page. International Journal of Engineering Research & Technology (IJERT), vol.1, pp.1-5..

Peng, Z., Xiu, X., Ming, Z. 2011. An Efficient Improved Strategy for the PageRank Algorithm. International Conference on Management and Service Science (MASS), IEEE, pp. 1-4.

Scarselli, F., Liang Yong, S., Gori, M., Hagenbuchner, M., Tsoi, A.C., Maggini, M. 2005. Graph Neural Networks for Ranking Web Pages. International Conference on Web Intelligence. Proceedings. The 2005 IEEE/WIC/ACM, pp.666- 672.

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Published

2017-02-15

How to Cite

Khonji, A., & Harounabadi, D. A. (2017). An Algorithm for Ranking Web Pages Based on Links and Ant Colony Algorithm. International Journal of Computer (IJC), 24(1), 37–42. Retrieved from https://www.ijcjournal.org/index.php/InternationalJournalOfComputer/article/view/821

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