A Novel Approach to Extract High Utility Itemsets from Distributed Databases

Authors

  • Kannimuthu Subramanian Department of IT, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu
  • Premalatha Kandhasamy Department of CSE, Bannari Amman Institute of Technology, Sathyamangalam, Tamil Nadu
  • Shankar Subramanian Department of IT, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu

Keywords:

ARM, data mining, distributed database, FUM, HUI, FUM-D, UMining, utility mining

Abstract

Traditional approaches in data mining focus on support and confidence measures which are just statistics based. Support and confidence measures which are based on the frequency count of the items enable us to derive the frequent itemsets. The frequency of the items as a single factor does not represent the interestingness of the items. To enhance the process of data mining tasks based on the value of the product, several researches were conducted. It resulted in utility mining which is an emerging field of research in data mining. In the recent years various data mining approaches have been implemented in order to find the high utility itemsets. The main objective of utility mining is to identify the itemsets with highest utilities, by considering the subjectively defined utility values, as set by the user. Existing methods based on utility mining concept focus on centralized systems where the data and associated processing is pertained to a particular location. As a further step ahead we try to implement the utility mining concept in a distributed environment. In this approach we use a sophisticated way of mining high utility itemsets using a Fast Utility Mining (FUM) algorithm.

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Published

2013-01-30

How to Cite

Subramanian, K., Kandhasamy, P., & Subramanian, S. (2013). A Novel Approach to Extract High Utility Itemsets from Distributed Databases. COMPUTING AND INFORMATICS, 31(6+), 1597–1615. Retrieved from https://www.cai.sk/ojs/index.php/cai/article/view/1333