Integration of OLAP and association rule mining

Author

Bawane, Gunwanti R. ; Deshkar, Prarthana

Author_Institution

Dept. of Comput. Sci. & Eng., Yeshwantrao Chavan Coll. of Eng., Nagpur, India

fYear

2015

Firstpage

1

Lastpage

4

Abstract

OLAP is a multidimensional view of complete data in the data store used for multidimensional analysis. It is the most practical approach used in the data warehouse for analytical process of large data and provides tools for analytical and statistical analysis of data. Association rule learning is a popular method for discovering user interested relations between variables in very large databases. Apriori_cube is advanced algorithm of traditional Apriori algorithm and is used to discover the association rules in multidimensional datasets. This algorithm is used to integrate OLAP and the Association rule mining and build a system which provides rules which can be further analyzed to take decisions regarding the market trends.

Keywords

data mining; statistical analysis; Apriori algorithm; Apriori_cube; OLAP integration; association rule mining; data store; multidimensional data view analysis; multidimensional datasets; statistical analysis; very large databases; Algorithm design and analysis; Association rules; Conferences; Itemsets; Market research; Apriori algorithm; Apriori_cube; Association rule; OLAP; frequent itemset;

fLanguage

English

Publisher

ieee

Conference_Titel

Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on

Conference_Location

Coimbatore

Print_ISBN

978-1-4799-6817-6

Type

conf

DOI

10.1109/ICIIECS.2015.7193123

Filename

7193123