International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 17 - Number 5 |
Year of Publication: 2011 |
Authors: J.R.Jeba, S.P.Victor |
10.5120/2214-2819 |
J.R.Jeba, S.P.Victor . A Novel Approach for finding Frequent Item Sets with Hybrid Strategies. International Journal of Computer Applications. 17, 5 ( March 2011), 30-33. DOI=10.5120/2214-2819
Frequent item sets mining plays an important role in association rules mining. Over the years, a variety of algorithms for finding frequent item sets in very large transaction databases have been developed. Therefore, a number of methods have been proposed recently to discover approximate frequent item sets. This paper proposes an efficient SMine (Sorted Mine) Algorithm for finding frequent item sets. This proposed method reduces the number of scans in the database. Our proposed SMine algorithm works well based on graph construction. At last we performed an experiment on a real dataset to test the run time of our proposed algorithm. The experiment showed that it was efficient for mining datasets.