Title :
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
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;
Conference_Titel :
Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-6817-6
DOI :
10.1109/ICIIECS.2015.7193123
