Efficient High Utility Top-K Frequent Pattern Mining from High Dimensional Datasets

Authors(3) :-J. Krishna, M. Rupesh Kumar Reddy, Dr. M. Rudra Kumar

High utility pattern mining can be defined as discovering sets of patterns that not only co-occurs but they carry high profit. In two-phase pattern mining an apriori algorithm is used for candidate generation. However candidate generation is costly and it is challenging problem that if number of candidate are huge then scalability and efficiency are bottleneck problems. As a rule, finding a fitting least utility edge by experimentation is a monotonous procedure for clients. In the event that min_util is set too low, an excessive number of HUIs will be produced, which may bring about the mining procedure to be exceptionally wasteful. Then again, if min_util is set too high, it is likely that no HUIs will be found. In this paper, we address the above issues by proposing another structure for top-k high utility thing set mining, where k is the coveted number of HUIs to be mined. Two sorts of proficient calculations named TKU (mining Top-K Utility thing sets) and TKO (mining Top-K utility thing sets in one stage) are proposed for mining such thing sets without the need to set min_util. We give an auxiliary examination of the two calculations with talks on their preferences and restrictions. Exact assessments on both genuine and manufactured datasets demonstrate that the execution of the proposed calculations is near that of the ideal instance of best in class utility mining calculations.

Authors and Affiliations

J. Krishna
AITS, Department of CSE Research Scholar, RU, Kurnool, India
M. Rupesh Kumar Reddy
M.Tech.,(PG Scholar), Department of CSE,Annamacharya Institute of Technology & Sciences, Rajampet, Kadapa, Andhra Pradesh, India
Dr. M. Rudra Kumar
Professor, Department of CSE, Annamacharya Institute of Technology & Sciences, Rajampet, Kadapa, Andhra Pradesh, India

Utility mining, high utility item set mining, top-k pattern mining, top-k high utility item set mining, Data mining, frequent itemset, transactional database.

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Publication Details

Published in : Volume 2 | Issue 4 | July-August 2017
Date of Publication : 2017-08-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 625-631
Manuscript Number : CSEIT1172485
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

J. Krishna, M. Rupesh Kumar Reddy, Dr. M. Rudra Kumar, "Efficient High Utility Top-K Frequent Pattern Mining from High Dimensional Datasets", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 4, pp.625-631, July-August-2017.
Journal URL : http://ijsrcseit.com/CSEIT1172485

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