IMS Manthan (The Journal of Mgt., Comp. Science & Journalism)

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Association Rule Mining with Hybrid-Dimension Datasets


Affiliations
1 Computer Department, Vidyalankar Institute of Technology, Wadala, Mumbai, India
     

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Hybrid dimension association rules mining algorithm satisfies the definite condition on the basis of multidimensional transaction database. Boolean Matrix based approach has been employed to generate frequent item sets in multidimensional transaction databases. When using this algorithm first time, it scans the database once and will generate the association rules. Apriori property is used in algorithm to prune the item sets. It is not necessary to scan the database again; it uses Boolean logical operations to generate the association rules.

Keywords

Association Rule, Hybrid Dimensional Association Rule, Relational Calculus, Multidimensional Transaction Database
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  • Association Rule Mining with Hybrid-Dimension Datasets

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Authors

Priyanka Pawar
Computer Department, Vidyalankar Institute of Technology, Wadala, Mumbai, India
Sachin Deshpande
Computer Department, Vidyalankar Institute of Technology, Wadala, Mumbai, India
Vipul Dalal
Computer Department, Vidyalankar Institute of Technology, Wadala, Mumbai, India

Abstract


Hybrid dimension association rules mining algorithm satisfies the definite condition on the basis of multidimensional transaction database. Boolean Matrix based approach has been employed to generate frequent item sets in multidimensional transaction databases. When using this algorithm first time, it scans the database once and will generate the association rules. Apriori property is used in algorithm to prune the item sets. It is not necessary to scan the database again; it uses Boolean logical operations to generate the association rules.

Keywords


Association Rule, Hybrid Dimensional Association Rule, Relational Calculus, Multidimensional Transaction Database

References