Efficient Association Rules Hiding Using Genetic Algorithms
نویسندگان
چکیده
منابع مشابه
Using Efficient Boolean Algorithms for Mining Association Rules
In this paper, we use transaction data as the source data of mining, and each transaction data contains a consumer ever buy items. We mine association rules from two aspects. One is to present a Boolean FP-tree algorithm to mine association rules with the Boolean computation according to the FP-tree algorithm and CDAR algorithm. The experiments show that the performances of our algorithm are fa...
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Association rule mining is interesting area of data mining research which discovers correlations between different item sets in a transaction database. Efforts have been made for efficient hiding of sensitive association rules, but these techniques do not consider the consequences such as loss of information, lost rules and increase in ghost rules production. In this paper, we propose improved ...
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Association rule mining problem (ARM) is a structured mechanism for unearthing hidden facts in large data sets and drawing inferences on how a subset of items influences the presence of another subset. ARM is computationally very expensive because the number of rules grow exponentially as the number of items in the database increase. This exponential growth is exacerbated further when data dime...
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association rules are among important techniques in data mining which are used for extracting hidden patterns and knowledge in large volumes of data. association rules help individuals and organizations take strategic decisions and improve their business processes. extracted association rules from a database contain important and confidential information that if published, the privacy of indivi...
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ژورنال
عنوان ژورنال: Symmetry
سال: 2018
ISSN: 2073-8994
DOI: 10.3390/sym10110576