International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 164 - Number 10 |
Year of Publication: 2017 |
Authors: Rina Raval |
10.5120/ijca2017913690 |
Rina Raval . F3 Algorithm for Association Rules. International Journal of Computer Applications. 164, 10 ( Apr 2017), 6-11. DOI=10.5120/ijca2017913690
Frequent pattern mining or association rule mining has been very fascinating research topic. It gives association rules which are nothing else but relationships amongst data. These relationships play vital role to make decision in market based analysis, medical applications, banking and many other organizations. Amongst several algorithms provided for frequent pattern mining, time necessitated is always very important aspect to be considered. The breakthrough approach named F3 algorithm, finds frequent patterns by considering quantity of individual item in single transaction rather than item’s presence. Afterwards it finds supplementary appealing patterns from profit of items. This approach not only reduces the time for finding frequent patterns, but also endow with new effective pat-terns which act as a key to improve business utility.