New Improved Algorithm for Mining Privacy - Preserving Frequent Itemsets | Zendy

Rashmi Awasthy | Zendy; Rajesh Shrivastava | Zendy; Bharat Solanki | Zendy

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New Improved Algorithm for Mining Privacy - Preserving Frequent Itemsets

Author(s) -

Rashmi Awasthy,

Rajesh Shrivastava,

Bharat Solanki

Publication year - 2011

Publication title -

international journal of computer science and informatics

Language(s) - English

Resource type - Journals

ISSN - 2231-5292

DOI - 10.47893/ijcsi.2011.1001

Subject(s) - data mining , database transaction , computer science , association rule learning , order (exchange) , transaction data , data warehouse , database , business , finance

Due to the increasing use of very large databases and data warehouses, mining useful information and helpful knowledge from transactions is evolving into an important research area. Frequent Itemsets (FI) Mining is one of the most researched areas of data mining. In order to mining privacy preserving frequent itemsets on large transaction database efficiently, a new approach was proposed in this paper. KeywordsData mining, frequent itemsets, privacy preserving

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