An Efficient Approach for Data Mining with Compressed Data

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-28 Number-5
Year of Publication : 2015
Authors : Mr.Vaibhav Kumar Sharma, Mr.Anil Gupta, Mr. B.L. Pal
  10.14445/22312803/IJCTT-V28P144

MLA

Mr.Vaibhav Kumar Sharma, Mr.Anil Gupta, Mr. B.L. Pal  "An Efficient Approach for Data Mining with Compressed Data". International Journal of Computer Trends and Technology (IJCTT) V28(5):222-227, October 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
In an era of knowledge explosion, the growth of data increases rapidly day by day. Since data storage is a limited resource, how to reduce the data space in the process becomes a challenge issue. Data compression provides a good solution which can lower the required space. Data mining has many useful applications in recent years because it can help users discover interesting knowledge in large databases. Existing compression algorithms are not appropriate for data mining. In this paper our main focus is on association rule mining and data pre-process with data compression. We proposed a knowledge discovery process from compressed databases in which data can be decomposed.

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Keywords
Association rule, Apriori Algorithm