International Research journal of Management Science and Technology

  ISSN 2250 - 1959 (online) ISSN 2348 - 9367 (Print) New DOI : 10.32804/IRJMST

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HIGH UTILITY ITEMSET MINING – APPROACHES AND ALGORITHMS

    1 Author(s):  MAHAK DHANDA

Vol -  8, Issue- 11 ,         Page(s) : 211 - 216  (2017 ) DOI : https://doi.org/10.32804/IRJMST

Abstract

Utility of an itemset in a transactional database delineates its profitability or importance or interestingness to the user. In many of the decision making problems ex. Retail market etc. utility of itemsets is paramount. Utility itemset mining has turned up as a subfield of data mining to target this area. This article surveys the various High-Utility Itemset Mining algorithms and approaches proposed till date.

1. Liu Y., et al..: A fast high utility itemsets mining algorithm. Proceedings of the 1st international workshop on Utility-based data mining, ACM, 90-99 (2005).
2. P. Fournier-Viger, C.W. Wu, S. Zida, V.S. Tseng.: FHM: faster high-utility itemset mining using estimated utility co-occurrence pruning, Found. Intell. Syst., Springer, 83–92(2014).
3. Liu, M., Qu, J.: Mining High Utility Itemsets without Candidate Generation. Proceedings of CIKM 2012, ACM,55–64 (2012).
4. J. Liu, K. Wang, B. Fung.: Direct Discovery of High Utility Itemsets without Candidate Generation,  IEEE 12th International Conference on Data Mining (ICDM), IEEE, 984-989, (2012).
5. Song, W., Liu, Y., Li, J.: BAHUI: fast and memory efficient mining of high utility itemsets based on bitmap. Int. J. Data Warehous. Min., 1–15 (2014).
6. C.F. Ahmed, S.K. Tanbeer, B.-S. Jeong, Y.-K. Lee.: Efficient Tree Structures for High Utility Pattern Mining in Incremental Databases, IEEE Trans. Knowledge and Data Eng., IEEE, 1708-1721, (2009).

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