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Artificial Bee Colony (ABC) Approach for Ranking Web Pages
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 99 - Number 1 |
| Year of Publication: 2014 |
| Authors: G. Anuradha, G. Lavanya Devi |
10.5120/17340-7482
|
G. Anuradha, G. Lavanya Devi . Artificial Bee Colony (ABC) Approach for Ranking Web Pages. International Journal of Computer Applications. 99, 1 ( August 2014), 35-39. DOI=10.5120/17340-7482
Abstract
The World Wide Web (WWW) is rapidly growing on all aspects and is a massive, explosive, data resource in the world. In information retrieval approach web Search engines are predominant tools for finding and getting access to the contents of web. The primary goal of Search engine is to provide relevant information to the users according to their needs, Usually Search engines gives large result set for a user's query. To limit the result list, it is necessary to assign ranking the web pages in an efficient and effective manner. Artificial Bee Colony (ABC) is one of the new approaches used to solve optimization problems. This paper proposes Artificial Bee Colony (ABC) approach as a new method for web mining particularly in ranking web pages. It considers users interest, total web site linkage and growth analysis rate are used to assign rank the web pages. Proposed ABC approach for ranking web pages is implemented and tested on real datasets. The experimental results shows efficiency of the proposed method compared with tradition page Rank Algorithm.
References
- Laxmi Choudhary, Bhawani Shankar Burdak. 2008," Role of Ranking Algorithms for Information Retrieval " Discrete Algorithms Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms; Pages: 1010-1018.
- Manju Patel1 and Shweta Modi. 2011," A Survey on Distributed Page Ranking", International Journal of Chemistry and Applications. ISSN 0974-3111 Volume 3, pp. 201-208
- Hema Dubey, Prof. B. N. Roy. 2011,"An Improved Page Rank Algorithm based on Optimized Normalization Technique", International Journal of Computer Science and Information Technologies, Vol. 2 (5) , 2183-2188
- http://www. cs. princeton. edu/chazelle/courses/BIB/ pagerank. htm
- E. Bonabeau, M. Dorigo, G. Theraulaz. 1999, "Swarm Intelligence: From Natural to Artificial Systems", New York, NY: Oxford University Press
- D. Karaboga, b. Akay. 2005, "Artificial bee colony (abc), harmony search and bees algorithms on Numerical optimization", Erciyes University, the dept. Of computer engineering, 38039, melikgazi, kayseri, turkiye
- Ashita S. Bhagade, Parag. V. Puranik. 2012, " Artificial Bee Colony (ABC) Algorithm for Vehicle Routing Optimization Problem", International Journal of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-2, Issue-2.
- Milos Subotic, "Artificial bee colony algorithm with multiple onlookers, for constrained optimization problems", Proceedings of the European Computing Conference
- V. Tereshko. 2000, "Reaction–diffusion model of a honeybee colony's foraging behavior", in: M. Schoenauer (Ed. ), Parallel Problem Solving from Nature VI,Lecture Notes in Computer Science, vol. 1917, Springer–Verlag, Berlin, , pp. 807–816.
- V. Tereshko, T. Lee. 2002, "How information mapping patterns determine foraging behaviour of a honeybee colony", Open Systems and Information Dynamics 181–193.
- V. Tereshko, A. Loengarov. 2005, Collective decision-making in honeybee foraging dynamics, Computing and Information Systems Journal 9 (3).
- www. alexa. com
- G. Anuradha, G. Lavanya Devi and M. S Prasad Babu. 2014, "Antrank: an ant colony algorithm for ranking web pages", ijettcs
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