Implementation of Algorithm for Finding Top-k High Utility Item sets

Authors

  • D. Swapna Assistant Professor, Computer Science and Engineering, BVRIT Hyderabad College of Engineering for Women
  • P. Hima Bindu Computer Science and Engineering, BVRIT Hyderabad College of Engineering for Women
  • P. Sri Ramya Computer Science and Engineering, BVRIT Hyderabad College of Engineering for Women
  • A. Siri Chandana Computer Science and Engineering, BVRIT Hyderabad College of Engineering for Women

Keywords:

Frequent mining, Association mining, High utility itemset mining, Top-k high utility mining, Utility mining.

Abstract

High utility item sets (HUIs) mining is an emerging technique in data mining. It helps in discovering all item
sets having a utility meeting a user-specified minimum utility threshold min_util. However, setting min_util appropriately
is a difficult problem for users. Finding an appropriate min_util by trial and error is a difficult process for users. If
min_util is set too low, too many itemsets will be generated, which takes large search space and may cause the mining
process to be very inefficient. On the other hand, if min_util is set too high, it is likely that no HUIs will be found. To
overcome this we have two phase mining techniques in which scalability and efficiency are bottleneck problems. To
solve this, we use an algorithm named TKO(Top-k utility itemsets in one phase) in which the high utility itemsets are
generated in one phase. It makes use of utility-list structure. It yields the top k utility itemsets where k is the user
specified value.

Published

2017-03-25

How to Cite

D. Swapna, P. Hima Bindu, P. Sri Ramya, & A. Siri Chandana. (2017). Implementation of Algorithm for Finding Top-k High Utility Item sets. International Journal of Advance Engineering and Research Development (IJAERD), 4(3), 681–684. Retrieved from https://ijaerd.com/index.php/IJAERD/article/view/2161