Data Mining and Knowledge Engineering

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

A New Approach to Discover Frequent Patterns Using FP-Graph Model


Affiliations
1 P.G.Department of Computer Science, Kongu Arts and Science College, Erode, Tamilnadu, India
2 K.S. Rangasamy College of Technology, Tiruchengode, Tamilnadu, India
     

   Subscribe/Renew Journal


In this paper an algorithm is proposed for mining frequent itemsets. This paper proposes a new framework to generate frequent Itemsets/Patterns. First, a partitioning technique is used to divide a transaction database TDB into n non-overlapping partitions. Second we use fp-graph model to discover frequent itemsets for each partition. Example illustrating the proposed approach is given. The characteristics of the algorithm are discussed.

Keywords

Data Mining, Frequent Patterns, Frequent Itemset, Partitioning Technique, FP-Graph, Association Rule.
User
Subscription Login to verify subscription
Notifications
Font Size

Abstract Views: 261

PDF Views: 1




  • A New Approach to Discover Frequent Patterns Using FP-Graph Model

Abstract Views: 261  |  PDF Views: 1

Authors

B. Jayanthi
P.G.Department of Computer Science, Kongu Arts and Science College, Erode, Tamilnadu, India
K. Duraiswamy
K.S. Rangasamy College of Technology, Tiruchengode, Tamilnadu, India

Abstract


In this paper an algorithm is proposed for mining frequent itemsets. This paper proposes a new framework to generate frequent Itemsets/Patterns. First, a partitioning technique is used to divide a transaction database TDB into n non-overlapping partitions. Second we use fp-graph model to discover frequent itemsets for each partition. Example illustrating the proposed approach is given. The characteristics of the algorithm are discussed.

Keywords


Data Mining, Frequent Patterns, Frequent Itemset, Partitioning Technique, FP-Graph, Association Rule.