Combining and Analysing Apriori and K-Means Algorithms for Efficient Data Mining on the Web

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-23 Number-1
Year of Publication : 2015
Authors : Nisha Rani,Yamini Chouhan
  10.14445/22312803/IJCTT-V23P107

MLA

Nisha Rani,Yamini Chouhan "Combining and Analysing Apriori and K-Means Algorithms for Efficient Data Mining on the Web". International Journal of Computer Trends and Technology (IJCTT) V23(1):31-34, May 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Web mining is the combination of data assembled by combining information mining techniques and procedures with data accumulated over the World Wide Web. Mining means extricating something helpful or important from a large no of datasets .Web mining is utilized to comprehend client conduct, assess the adequacy of a specific Web website, and help evaluate the accomplishment of a specified task. The proposed work is aimed to find a solution for generating different frequent item sets at each site in a distributed network. Apriori algorithm is a very popular algorithm for data mining that is dependent upon reducing infrequent item from item sets for mining useful data. Apriori algorithm can be very slow because of no of transactions. In order to increase the efficiency of the algorithm the initial item set is further clustered using K-Means algorithm. Cloud computing and data mining are emerging technologies dealing with major issues such as security and scalability and efficiency. The proposed work aims to increase efficiency of both the technologies.

References
[1] Agrawal R, Srikant R (1994) Fast algorithms for mining associationrules.In:Proceedings of the 20th VLDB conference, pp 487–499
[2] Mining Association Rules between Sets of Items in Large Databases:Rakesh Agrawal ,Tomasz Imielinski,Arun SwamiACM SIGMOD ConferenceWashington DC, USA, May 1993
[3] G.K. Gupta,Introduction to data mining with case studies:Prentics Hall of India, New Delhi, 2006 [4] Han, David, et al. Principles of Data Mining: MIT press. Cambridge, 2001.
[5] Mining Association Rules between Sets of Items in Large Databases:Rakesh Agrawal ,Tomasz Imielinski,Arun SwamiACM SIGMOD ConferenceWashington DC, USA, May 1993
[6] Fast Algorithms for Mining Association Rules: Rakesh Agrawal Ramakrishnan Srikant VLDB Conference Santiago, Chile, 1994
[7] High Performance Data Mining Using the Nearest Neighbor Join Christian Böhm Florian Krebs
[8] A Review of various k-Nearest Neighbor Query Processing Techniques :International Journal of Computer Applications (0975 – 8887) Volume 31–No.7, October 2011
[9] Mining of Meteorological Data Using Modified Apriori Algorithm,European Journal of Scientific Research ISSN 1450-216X Vol.47 No.2 (2010), pp.295-308EuroJournals Publishing, Inc. 201
[10] Fast Algorithms for Mining Association Rules: Rakesh Agrawal Ramakrishnan Srikant VLDB Conference Santiago, Chile, 1994High Performance
[11] Data Mining Using the Nearest Neighbor Join Christian Böhm Florian KrebsA Review of various k-Nearest Neighbor Query Processing
[12] Top 10 algorithms in data mining, Xindong Wu, Springer- 2007
[13] Han, Jiawei and Kamber, Micheline, Data Mining Concepts and Techniques. Morgan Kaufman Publishers. San Fransisco 2000.

Keywords
Cloud Computing, Apriori Algorithm ,K-Means Algorithm.