Mining association rules between values across attributes in data streams

dc.contributor.author	Naik, S.B.
dc.contributor.author	Pawar, J.D.
dc.date.accessioned	2018-10-09T09:29:19Z
dc.date.available	2018-10-09T09:29:19Z
dc.date.issued	2017
dc.identifier.citation	International Conference on Computational Intelligence in Data Science (ICCIDS), 2-3 Jun 2017. 2017; 6pp.	en_US
dc.identifier.uri	http://dx.doi.org/10.1109/ICCIDS.2017.8272634
dc.identifier.uri	http://irgu.unigoa.ac.in/drs/handle/unigoa/5437
dc.description.abstract	In this paper we propose a framework and approach to model events as elements of data stream and perform analysis to group values of attribute similar to each other within an attribute and find associations between clusters of values across two attributes. Experiments have been performed on both synthetic and real data sets.	en_US
dc.publisher	IEEE	en_US
dc.subject	Computer Science and Technology	en_US
dc.title	Mining association rules between values across attributes in data streams	en_US
dc.type	Conference article	en_US