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Title: hiding sensitive association rules with limited side effects source code
Page Link: hiding sensitive association rules with limited side effects source code -
Posted By:
Created at: Monday 19th of November 2012 02:35:40 PM
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Title: association rules management decision
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Posted By:
Created at: Sunday 23rd of December 2012 05:12:58 PM
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Title: Privacy Preserving Association Rules by Using Greedy Approach
Page Link: Privacy Preserving Association Rules by Using Greedy Approach -
Posted By: seminar addict
Created at: Saturday 21st of January 2012 02:36:42 PM
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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 ....etc

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Title: code for knowledge based interactive postmining of association rules using ontologies
Page Link: code for knowledge based interactive postmining of association rules using ontologies -
Posted By:
Created at: Wednesday 26th of December 2012 03:12:29 AM
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Title: does skinput technology has side effects
Page Link: does skinput technology has side effects -
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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: smart paper boy
Created at: Tuesday 30th of August 2011 12:08:35 PM
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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 ....etc

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Title: Mining Weighted Association Rules without Preassigned Weights
Page Link: Mining Weighted Association Rules without Preassigned Weights -
Posted By: project topics
Created at: Monday 02nd of May 2011 12:40:06 PM
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Mining Weighted Association Rules without Preassigned Weights- IEEE 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 l ....etc

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Title: hiding sensitive association rules with limited side effects source code in java
Page Link: hiding sensitive association rules with limited side effects source code in java -
Posted By:
Created at: Sunday 09th of December 2012 01:34:13 PM
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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: jpmahadev
Created at: Saturday 24th of April 2010 01:22:28 AM
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Title: Hiding Sensitive Association Rules with Limited Side Effects
Page Link: Hiding Sensitive Association Rules with Limited Side Effects -
Posted By: seminar paper
Created at: Wednesday 14th of March 2012 06:33:29 PM
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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 ....etc

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