An Efficient Method to Identify the Most Frequent Item Sets Using Database Count Algorithm and Effective Aco Algorithm in a Peer to Peer Network
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2014 by IJCTT Journal|
|Year of Publication : 2014|
|Authors : S.Veena, DR.P.Rangarajan|
|DOI : 10.14445/22312803/IJCTT-V17P153|
S.Veena, DR.P.Rangarajan "An Efficient Method to Identify the Most Frequent Item Sets Using Database Count Algorithm and Effective Aco Algorithm in a Peer to Peer Network". International Journal of Computer Trends and Technology (IJCTT) V17(6):300-303, Nov 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
A peer-to-peer (P2P) network is one that does not have fixed clients and servers but a number of peer nodes that function as both clients and servers to the other nodes in the network. Association Rule Mining can be used for discovering hidden relationship between items stored in various nodes in the network . By given a user-specified threshold, also known as minimum support, the mining of association rules can discover the complete set of frequent patterns. In this paper, a Database count algorithm is used to mine the local frequent item sets and then generate the global frequent item sets from a Peer to peer network. Then the global item sets are optimized by using the Effective Ant colony Optimization algorithm to generate the most frequent item sets.
 Kanishka Bhaduri, Kamalika Das, Kun Liu, Hillol Kargupta, “Distributed Identification of Top-l Inner Product Elements and its Application in a Peer-to-Peer Network”, CIKM , 2006.
 K. Liu, H. Kargupta, and J. Ryan, “Random Projection-Based Multiplicative Data Perturbation for Privacy Preserving Distributed Data Mining,” IEEE Trans. Knowledge and Data Eng., vol. 18, no. 1, pp. 92-106, Jan. 2006.
 Rakesh Agrawal, T. Imieli?ski, A. Swami, "Mining association rules between sets of items in large databases". In: Proceedings of the 1993 ACM SIGMOD international conference on Management of data - SIGMOD `93, 1993 pp. 207-216.
 Sanjeev Rao, Prianka Gupta, “Implementing Improved Algorithm Over APRIORI Data Mining Association Rule Algorithm”, In: proceeding of IJCST, ISSN 0876-8491, VOL.3, Issue 1, Jan-March 2012.
 B. Babcock and C. Olston, “Distributed Top-k Monitoring,” Proc. ACM SIGMOD ’03, pp. 28-39, 2003.
 Kamalika Das, Kanishka Bhaduri, Kun Liu, and Hillol Kargupta, “Distributed Identification of Top-l Inner Product Elements and Its Application in a Peer-to-Peer Network,” IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 19, NO. 4, 2008.
 S. Rao, R. Gupta, “Implementing Improved Algorithm Over APRIORI Data Mining Association Rule Algorithm”, International Journal of Computer Science And Technology, pp. 489-493, Mar. 2012.
 Cheung.D.W,”A fast distributed algorithm for mining association rules”,4th International Conference on Parallel and Distributed Information Systems,1996,P31-42.
 Thabet Slimani ,” Efficient Analysis of Pattern and Association Rule Mining Approaches “ IJITCS Vol. 6, No. 3, February 2014
 M. Dorigo, Gianni Di Caro, and Luca M. Gambardella. Ant Algorithms for Discrete Optimization. Technical Report Tech. Rep. IRIDIA/98-10, IRIDIA, Universite Libre de Bruxelles, Brussels, Belgium, 1998.
 M. Dorigo and M. Maniezzo and A. Colorni. The Ant Systems: An Autocatalytic Optimizing Process. Revised 91-016, Dept. of Electronica, Milan Polytechnic, 1991.
 M. Dorigo and G. Di Caro. New Ideas in Optimisation. McGraw Hill, London, UK, 1999.
Peer to Peer network, Database Count algorithm, Effective Ant Colony Optimization algorithm.