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Reseach Article

Review on Hiding the Sensitive High Utility Itemsets

by S.kannimuthu, S.gunasekaran, S.roopa
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 13
Year of Publication: 2015
Authors: S.kannimuthu, S.gunasekaran, S.roopa
10.5120/21130-3938

S.kannimuthu, S.gunasekaran, S.roopa . Review on Hiding the Sensitive High Utility Itemsets. International Journal of Computer Applications. 119, 13 ( June 2015), 30-33. DOI=10.5120/21130-3938

@article{ 10.5120/21130-3938,
author = { S.kannimuthu, S.gunasekaran, S.roopa },
title = { Review on Hiding the Sensitive High Utility Itemsets },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 13 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 30-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number13/21130-3938/ },
doi = { 10.5120/21130-3938 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:03:58.005085+05:30
%A S.kannimuthu
%A S.gunasekaran
%A S.roopa
%T Review on Hiding the Sensitive High Utility Itemsets
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 13
%P 30-33
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The Association Rule Mining is the traditional mining technique which identifies the frequent itemsets from the databases and this technique generates the rules by considering the each items. The traditional association rule mining fails to obtain the infrequent itemsets with higher profit. Since association rule mining technique treats all the items in the database equally by considering only the presence of items within the transaction. The above problem can be solved using the Utility Mining technique. The Utility Mining technique identifies the product combinations with high profit but low frequency itemsets in the transactional database. Hiding High Utility Itemsets (HUIs) is the main challenges faced in the utility mining. In this paper, a detailed discussion about the traditional Association Rule Mining and the various algorithms involved in Utility Mining is explained.

References
  1. Rajalakshmi selvaraj and Venu Madhav Kuthadi, 2013 A Modified Hiding High Utility Item First Algorithm(HHUIF) with Item Selector(MHIS) for Hiding Sensitive Itemsets in International Journal of Innovative Computing and Control.
  2. Ying Liu, wei-Keng Liao, Alok Choudhary, 2005 A Fast Itemsets Mining Algorithm, in UBDM'05, Chicago ,USA .
  3. Hong Yao, Howard J. Hamilton, 2005 Mining itemset utilities from transaction database, in ELSEVIER .
  4. Jianying Hu, Aleksandra Mojsilovic, 2007 High-utility pattern mining: A method for discovery of high-utility item sets, in pattern recognition ELSEVIER .
  5. Chung-jung Chu, Vincent S. Tseng, Tyne Liang, 2008 An efficient algorithm for mining temporal high utility itemsets from data streams, in science direct, the journal of system and software, ELSEVIER.
  6. Jieh-Shan Yeh, Po-Chiang Hsu, 2010 HHUIF and MSICF: Novel algorithms for privacy preserving utility mining, in expert systems with application, ELSEVIER .
  7. Cheng Wei Wu, Bai-En Shie, Philip S. Yu, Vincent S. Tseng, 2012 Mining Top-K High Utility Itemsets, KDD'12, Beijing, china.
  8. Dongwon Lee, Sung-Hyuk Park, Songchun Moon, 2012 Utility-based association rule mining: A marketing solution for cross-selling", in expert systems with applications ELSEVIER.
  9. Chun-Wei Lin, Tzung-Pei Hong, Hung-Chuan Hsu, 2014 Research article- Reducing side effects of hiding sensitive itemsets in privacy preserving data mining, in Hindawi publishing corporation The scientific world journal.
  10. Guo-cheng Lan, Tzung-pei Hong, Jen-peng Huang, Vincent S. Tseng, 2013 On-shelf utility mining with negative item values, in expert systems with applications, ELSEVIER .
  11. Chun-Wei Lin, Tzung-Pei Hong, Jia-Wei Wong, Guo-cheng Lan, wen-yang Lin, 2014 A GA-Based Approach to Hide Sensitive High Utility Itemsets, in Hindawi publishing corporation, the scientific world journal.
  12. Chun-Wei-Lin, Guo-Cheng Lan, Tzung-pei Hong, 2012 An incremental mining algorithm for high utility itemsets", in Expert system with applications ELSEVIER
  13. V. Ciriani, S. De Capitani di Vimercati, S. Foresti, and P. Samarati, 2008 K-Anonymous Data Mining: A survey in Springer US, Advances in Database Systems .
Index Terms

Computer Science
Information Sciences

Keywords

Association rule mining Data mining High utility itemsets utility mining.