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Title: hiding sensitive association rules with limited side effects source code
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Posted By: vikrant kr. dubey
Created at: Friday 06th of October 2017 03:10:50 PM
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Title: association rules management decision
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Posted By: niky.siva
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Title: code for knowledge based interactive postmining of association rules using ontologie
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Posted By: prem9823
Created at: Thursday 17th of August 2017 06:39:23 AM
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Title: Hiding Sensitive Association Rules with Limited Side Effects
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Posted By: throttle
Created at: Thursday 17th of August 2017 08:21:05 AM
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Hiding Sensitive Association Rules with Limited Side Effects

Abstract:
Data mining techniques have been widely used in various applications. However, the misuse of these techniques may lead to the disclosure of sensitive information. Researchers have recently made efforts at hiding sensitive association rules. Nevertheless, undesired side effects, e.g., non-sensitive rules falsely hidden and spurious rules falsely generated may be produced in the rule hiding process. In this paper, we present a nov ....etc

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Title: HIDING SENSITIVE INFORMATION
Page Link: HIDING SENSITIVE INFORMATION -
Posted By: mukesh9660
Created at: Thursday 05th of October 2017 05:34:06 AM
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1.1 ABOUT HIDING SENSITIVE:
Large repositories of data contain sensitive information which must be protected against unauthorized access. Here, we are going to hide sensitive information in large database in order to reduce modifications in database and reduce unwanted side effects. e.g., nonsensitive rules falsely hidden and spurious rules falsely generated may be produced in the rule hiding process. Here, we investigate confidentiality issues of a broad category of rules, which are called association rules. If t ....etc

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Title: Mining Weighted Association Rules without Preassigned Weights
Page Link: Mining Weighted Association Rules without Preassigned Weights -
Posted By: SHAFIN
Created at: Thursday 17th of August 2017 08:20:07 AM
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Mining Weighted Association Rules without Preassigned Weights- IEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 20, NO. 4, JAVA
Abstract
Association rule mining is a key issue in data mining. However, the classical models ignore the difference between the transactions, and the weighted association rule mining does not work on databases with only binary attributes. In this paper, we introduce a new measure w-support, which does not require preassigned weights. It takes the quality of transactions into consideration using link ....etc

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Title: Privacy Preserving Association Rules by Using Greedy Approach
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Posted By: pravy.mdu
Created at: Thursday 05th of October 2017 04:59:37 AM
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Privacy Preserving Association Rules by Using Greedy Approach



Introduction
In the data mining, the most well-known method is the
Apriori algorithm. Since the Apriori algorithm is costly to find
candidate itemsets, there are many variants of Apriori that
differ in how they check candidate itemsets against the
database . For example, Zaki et al. presented the
algorithms MaxEclat and CHARM for identifying maximal
frequent itemsets. Furthermore, in employed an effic ....etc

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Title: An Adaptive Algorithm for Incremental Mining of Association Rules
Page Link: An Adaptive Algorithm for Incremental Mining of Association Rules -
Posted By: bijoshmohan
Created at: Thursday 05th of October 2017 05:13:39 AM
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Abstract
The association rules represent an important class of knowledge that can be discovered from data warehouses. Current research efforts are focused on inventing efficient ways of discovering these rules from large databases. As databases grow, the discovered rules need to be verified and new rules need to be added to the knowledge base. Since mining afresh every time the database grows is inefficient, algorithms for incremental mining are being investigated. Their primary aim is to avoid or minimize scans of the older database b ....etc

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Title: validation of mining association rules with hierarchical clustering
Page Link: validation of mining association rules with hierarchical clustering -
Posted By: sreeraju
Created at: Thursday 05th of October 2017 05:30:23 AM
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