Combining and Analysing Apriori and K-Means Algorithms for Efficient Data Mining on the Web
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International Journal of Computer Trends and Technology (IJCTT) |  |
| © 2015 by IJCTT Journal | ||
| Volume-23 Number-1 |
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| Year of Publication : 2015 | ||
| Authors : Nisha Rani,Yamini Chouhan | ||
| DOI : 10.14445/22312803/IJCTT-V23P107 |
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.
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Keywords
Cloud Computing, Apriori Algorithm ,K-Means Algorithm.