Integration of OLAP and Association rule mining

被引：0
|
作者：
Bawane, Gunwanti R. [1 ]
Deshkar, Prarthana [1 ]
机构：
[1] Yeshwantrao Chavan Coll Engn, Dept Comp Sci & Engg, Nagpur, Maharashtra, India
来源：
2015 INTERNATIONAL CONFERENCE ON INNOVATIONS IN INFORMATION, EMBEDDED AND COMMUNICATION SYSTEMS (ICIIECS) | 2015年
关键词：
OLAP; Association rule; Apriori algorithm; Apriori_cube; frequent itemset;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
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收藏
页数：4
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