slugA Novel Approach of Association Mining with Apriori Algorithm to Extract the Frequent Itemsetset in OOD

Abstract

Most Of the organization have major requirement of Distributed Centralized database system. Each user presents at specification location access the dataset according to his requirement. It means only the partial information is required for each database location. Because of this instead of provide the complete database information to each user only the selected information is provided, this concept is called partitioning. The partitioning can be horizontal or the vertical. Some times because of the security reasons it is required to hide the sensitive information from user, in such also the partition is performed. The presented work is an intelligent approach that will perform the analysis on the user data requirement and accordingly the partition will be performed and the data information present to the user. In this proposed approach we are providing a dynamic approach to create dynamic partitions of the database on the basis of their frequent requirement. The proposed approach will perform an association rule mining along with Apriori Algorithm. The proposed algorithm will return the significant results in efficient Time.

Authors and Affiliations

Rekha Gulia

Keywords

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  • EP ID EP17771
  • DOI -
  • Views 381
  • Downloads 11

How To Cite

Rekha Gulia (2014). slugA Novel Approach of Association Mining with Apriori Algorithm to Extract the Frequent Itemsetset in OOD. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(2), -. https://www.europub.co.uk/articles/-A-17771