Review on Hiding the Sensitive High Utility Itemsets
نویسندگان
چکیده
منابع مشابه
Review on Hiding the Sensitive High Utility Itemsets
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 ...
متن کاملFast algorithms for hiding sensitive high-utility itemsets in privacy-preserving utility mining
High-Utility Itemset Mining (HUIM) is an extension of frequent itemset mining, which discovers itemsets yielding a high profit in transaction databases (HUIs). In recent years, a major issue that has arisen is that data publicly published or shared by organizations may lead to privacy threats since sensitive or confidential informationmay be uncovered by data mining techniques. To address this ...
متن کاملA Review of Mining High Utility Itemsets
Recently, high utility pattern or itemset mining has become the most important research issues in data mining. In high utility itemset mining, the profit values for every item are considered. Generating high utility itemsets from a set of transactions in horizontal data format is a common practice. We hereby present the study of issues related to the different structures used and algorithms for...
متن کاملA GA-Based Approach to Hide Sensitive High Utility Itemsets
A GA-based privacy preserving utility mining method is proposed to find appropriate transactions to be inserted into the database for hiding sensitive high utility itemsets. It maintains the low information loss while providing information to the data demanders and protects the high-risk information in the database. A flexible evaluation function with three factors is designed in the proposed a...
متن کاملMining Minimal High-Utility Itemsets
Mining high-utility itemsets (HUIs) is a key data mining task. It consists of discovering groups of items that yield a high profit in transaction databases. A major drawback of traditional high-utility itemset mining algorithms is that they can return a large number of HUIs. Analyzing a large result set can be very time-consuming for users. To address this issue, concise representations of high...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2015
ISSN: 0975-8887
DOI: 10.5120/21130-3938