FINDING HIGH UTILITY ITEMSETS OVER DYNAMIC TRANSACTIONAL DATABASE USING UP-GROWTH AND UP-GROWTH+ ALGORITHM

Authors

  • Ms. Anita A. Bhosale Computer Sci and Engg Dept Annasaheb Dange College of Engg Ashta, Sangli, India
  • Ms.Pallavi S.Kadam Computer Sci and Engg Dept Annasaheb Dange College of Engg Ashta, Sangli, India
  • Mr. Siddheshwar V. Patil Information Technology Dept Annasaheb Dange College of Engg Ashta, Sangli, India

Keywords:

Data mining, High utility mining, Incremental mining

Abstract

Mining high utility itemsets is an important research area in data mining. Finding itemsets with high utility like profit from database is known as high utility itemset mining. Different algorithms have been work on this area, but some of them have problem of generating large number of Potential High Utility Itemsets (PHUIs). Due to this performance of mining is minimized in case of execution time. In this paper we have focus on UP-Growth and UP-Growth+ algorithm which overcomes this limitation. This technique uses tree based data structure, UP-Tree for generating high utility itemsets with two scan of database. In this paper we have extend the working of these algorithms on incremental database because these existing algorithms have consider only static database. This limitation has covered in our system. When database is updated, our system regenerates UP-tree efficiently and generates high utility itemsets from dynamic database. Also we have compared the performance of both algorithms.

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Published

2021-03-27

Issue

2016: ICCCES

Section

Articles

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