Implementation of Efficient Algorithms for Mining Top-K High Utility Item sets
Keywords:
Utility mining, Mining Top-k HUI ,High Utility Itemset , Top-k framework, TKU,TKO.Abstract
Popular problem in data mining, which is called 'high-utility itemset mining' or more generally utility mining. High Utility Itemsets which are itemsets having a utility meeting a user-specified minimum utility threshold value i.e min_util. The main objective of utility mining is to find item sets with highest utilities , by considering profit, quantity, cost or any other user preferences. Research has been carried out in area of mining HUI's. Various techniques have been applied. The main problem with setting threshold value which is mostly user specific, is it needs to be appropriate. In Order to set most appropriate or right Threshold value for mining HUI's ,user needs to do trial & error which in turn is time consuming & tedious process, because if min_util is set too low , system will result in getting large data of HUI , which in turn makes system ineffective for the purpose of HUI. If we set min_util too high , this will result in getting small amount or no HUI's. Thus setting minimum threshold value is difficult. The proposed system is following Top-k framework for mining top-k HUI's, which is using two algorithms TKU (mining top-k utility itemsets) & TKO (mining top-k in one phase),without setting min_util threshold.
References
- R. Agrawal and R. Srikant, Fast Algorithms for Mining Association Rules,"Proc. 20th Intl Conf. Very L 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 Trans. Knowledge nd Data Eng., vol. 21, no. 12, pp. 17081721, Dec. 2009.
- K. Chuang, J. Huang, and M. Chen, Mining topk frequent patterns in the presence of the memory constraint, "VLDB J., vol. 17, pp. 13211344, 2008.
- R. Chan, Q. Yang, and Y. Shen, Mining highutility itemsets,"in Proc. IEEE Int. Conf. Data Mining, 2003, pp. 1926.
- FournierViger and V. S. Tseng, Mining topk sequential rules, "in Proc. Int. Conf. Adv. Data Mining Appl., 2011, pp. 180194.
- P. FournierViger, C. Wu, and V. S. Tseng, Mining topk association rules, "in Proc. Int. Conf. Can. Conf. Adv. Artif. Intell., 2012, pp. 6173
- P. FournierViger, C. Wu, and V. S. Tseng, Novel concise representations of high utility itemsets using generator patterns,"Iin Proc. Int. Conf. Adv. Data Mining Appl. Lecture Notes Comput. Sci., 2014, vol. 8933, pp. 3043
- J. Han, J. Pei, and Y. Yin, Mining frequent patterns without candidate generation,"in Proc. ACM SIGMOD Int. Conf. Manag. Data, 2000, pp. 112.
- J. Han, J. Wang, Y. Lu, and P. Tzvetkov, Mining topk frequent closed patterns without minimum support,"in Proc. IEEE Int. Conf. Data Mining, 2002, pp. 211218.
- S. Krishnamoorthy, LPruning strategies for mining high utility itemsets, "Expert Syst. Appl., vol. 42, no. 5, pp. 23712381, 2015.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT
This work is licensed under a Creative Commons Attribution 4.0 International License.