Frequent itemsets mining using vertical index list

Author

Sahaphong, Supatra

Author_Institution

Dept. of Comput. Sci., Ramkhamhaeng Univ., Bangkok, Thailand

fYear

2009

fDate

8-11 Aug. 2009

Firstpage

480

Lastpage

484

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICCSIT.2009.5234824

Filename

5234824