MARCMV: Mining Multi-View Association Rules from Clustered Multi-Views

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International Journal of Computational and Experimental Science Engineering
Volume:9 Issue:2
MARCMV: Mining Multi-View Association Rules from Clustered Multi-Views

MARCMV: Mining Multi-View Association Rules from Clustered Multi-Views

Authors : Shadi AL SHEHABI, Meltem YILDIRIM IMAMOGLU

Pages : 141-149

Doi:10.22399/ijcesen.1292987

View : 34 | Download : 41

Publication Date : 2023-06-30

Article Type : Research Paper

Abstract :Data mining involves examining vast quantities of data to uncover valuable insights that can be utilized for making informed decisions and driving business objectives. The study focuses on the task of finding relationships between features belonging to two different views using multi-view model, and proposes a novel approach called MARCMV. This approach extracts multi-view association rules from different views of the same data set using multi-clustering neural model. The study finds that MARCMV outperforms conventional symbolic methods in terms of association rule quality and running time.
Keywords : Multi view, Clustering, MultiSOM, MARCMV approach, Multi view association rule

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