Author : R. Sheeba Mary Ananthi 1
Date of Publication :27th April 2018
Abstract: In recent era, High Utility Itemset Mining (HUIM) is an emerging critical research topic. In traditional approach, the items which occur frequently together are extracted from a database. But the frequency of Itemset is not sufficient to reflect the actual utility. Utility mining is an extension of frequent Itemset mining by considering the utility of an item. Utility Mining is the process of discovering all item sets whose utility values are equal to or greater than the user specified threshold in a transaction database. Utility Mining covers all aspects of economic utility in data mining and helps in direction of itemset having high utility. The main objective of high utility itemset mining is to find the itemset having maximum utility values. We can extract the high utility from rare itemsets, irregular occurrence, from different discount strategies. In this paper, we present a various algorithms for High Utility Mining to promote business activities
Reference :
-
- J. Pillai, O.P. Vyas, B. Mulgrew, “User centric approach to itemset utility mining in Market Basket Analysis,” International Journal of Computer Sciences and Engineering, pp.393-400, July 2011.
- J. Pillai, O.P. Vyas, “Overview of Itemset Utility Mining and its Applications,” International Journal of Computer Applications, pp. 9–13, 2010.
- K. Amphawan, P. Lenca, A. Jitpattanakul, and A. Surarerks, “Mininghigh utility itemsets with regular occurrence,” Journal of ICT Research and Applications, vol. 10, no. 2, pp. 153–176, 2016.
- V. S. Tseng, B.E. Shie, C.W. Wu, and P. S. Yu, “Efficient algorithms for mining high utility itemsets from transactional databases,” IEEE Transactions on Knowledge and Data Engineering, vol. 25, no. 8, pp. 1772–1786, 2013.
- C. F. Ahmed, S. K. Tanbeer, B.S. Jeong, and Y.K. Lee, “Efficient tree structures for high utility pattern mining in incremental databases,” IEEE Transactions on Knowledge and Data Engineering, vol. 21, no. 12, pp. 1708–1721, 2009.
- P. Fournier-Viger, “FHN: Efficient mining of high-utility itemsets within negative unit profits,” Advanced Data Mining and Applications, pp. 16-29, 2014.
- H. Yao and H. J. Hamilton, “Mining itemset utilities from transaction databases,” Data and Knowledge Engineering, vol. 59, no. 3, pp. 603–626, 2006.
- C.W. Lin, T.P. Hong, and W.H. Lu, “An effective tree structure for mining high utility itemsets,” Expert Systems with Applications, vol. 38, no. 6, pp. 7419–7424, 2011.