Title :
Frequent itemsets mining using vertical index list
Author :
Sahaphong, Supatra
Author_Institution :
Dept. of Comput. Sci., Ramkhamhaeng Univ., Bangkok, Thailand
Abstract :
In this paper, the author propose a new approach to mine all frequent itemsets that performs database scanning only once to construct data structure. This structure uses the conceptual of vertical data layout to contain transaction data. The changing of minimal support is not effected by the data structure and rescan of database is not required. The proposed algorithm has the ability to find frequent itemsets without generation of candidate itemsets. It obtains complete and correct frequent itemsets. The examples of all definitions and correctness proving are provided.
Keywords :
data mining; data structures; database indexing; set theory; data structure; database scanning; frequent itemset mining; vertical data layout; vertical index list; Association rules; Bioinformatics; Clustering algorithms; Computer science; Data mining; Data structures; Economic forecasting; Indexes; Itemsets; Transaction databases; Algorithm; Association rule mining; Data minin; Frequent itemsets mining; Vertical data layout;
Conference_Titel :
Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-4519-6
Electronic_ISBN :
978-1-4244-4520-2
DOI :
10.1109/ICCSIT.2009.5234824
