loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
18th International Conference on Database and Expert Systems Applications (DEXA 2007)
Frequent Pattern Mining using Bipartite Graph
Regensburg, Germany
September 03-September 07
ISBN: 0-7695-2932-1
Duck Jin Chai, Chungbuk Information Technology Center, Korea
Long Jin, Chungbuk Information Technology Center, Korea
Buhyun Hwang, Chonnam National University, Korea
Keun Ho Ryu, Chungbuk National University, Korea
In this paper, we propose an efficient ALIB algorithm that can find frequent patterns by only onetime database scan. Frequent patterns are found without generation of candidate sets using LIB-graph. LIB-graph is generated simultaneously when the database is scanned for 1-frequent items generation. LIB-graph represents the relation between 1-frequent items and transactions including the 1-frequent items. That is, LIB-graph compresses database information into a much smaller data structure. We can quickly find frequent patterns because the proposed method conducts only onetime database scan and avoids the generation of candidate sets. Our performance study shows that the ALIB algorithm is efficient for mining frequent patterns, and is faster than the FP-growth.
Citation:
Duck Jin Chai, Long Jin, Buhyun Hwang, Keun Ho Ryu, "Frequent Pattern Mining using Bipartite Graph," dexa, pp.182-186, 18th International Conference on Database and Expert Systems Applications (DEXA 2007), 2007
Usage of this product signifies your acceptance of the Terms of Use.