A Two step optimized spatial Association rule Mining Algorithm by hybrid evolutionary algorithm and cluster segmentation.

α
Dr. J.Arunadevi
Dr. J.Arunadevi MCA.,M.Phi.,Ph.D( Comp.Sci.), MBA
σ
Dr.V.Rajamani
Dr.V.Rajamani
α Madurai Kamaraj University

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A Two step optimized spatial Association rule Mining Algorithm by hybrid evolutionary algorithm and cluster segmentation.

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Abstract

A novel two step approach by adopting hybrid evolutionary algorithm with cluster segmentation for Spatial Association Rule mining (SAR) is presented in this paper.Here first step concentrates on the optimization of SAR using the hybrid evolutionary algorithm which uses genetic algorithm and ant colony optimization (ACO). Multi objective genetic algorithm is used to provide the diversity of associations. ACO is performed to come out of local optima. In the second step, cluster the generated association rules used for the target group segmentation. Preferential based segmentation of the women of various groups belongs to the Madurai city, Tamilnadu, India. Here, number of rules generated by the first step of our SAR is minimized, also time generation for the rules are also minimized. Lift ratio increased for the generated rules.

References

30 Cites in Article
  1. R Agarwal,R Srikant (1994). fast Algorithms for mining association rules in large databases.
  2. Margaret Dunham,S Sridhar (2006). Advanced Topics.
  3. J Yoo,S Shekhar,M Celik (2005). A Joinless Approach for Co-location Pattern Mining: A Summary of Results.
  4. Jin Yoo,Shashi Shekhar,John Smith,Julius Kumquat (2004). A partial join approach for mining co-location patterns.
  5. M Appice,M Berardi,M Ceci,D Malerba (2005). Mining and Filtering Multi-level Spatial Association Rules with ARES.
  6. J Mennis,J Liu (2005). Mining Association Rules in Spatio-Temporal Data: An Analysis of Urban Socioeconomic and Land Cover Change.
  7. Krzysztof Koperski,Jiawei Han (1995). Discovery of spatial association rules in geographic information databases.
  8. Vania Bogorny,Sandro Da Silva Camargo,Paulo Engel,Luis Alvares (2006). Towards Elimination of Well Known Geographic Patterns in Spatial Association Rule Mining.
  9. Alex Freitas (1155). A Survey of Evolutionary Algorithms for Data Mining and Knowledge Discovery.
  10. S Dehuri,A Jagadev,A Ghosh,R Mall (2006). Multi-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations.
  11. P Peter,Venansius Wakabi-Waiswa,Baryamureeba Extraction of Interesting Association Rules Using Genetic Algorithms.
  12. Anna Bicchi,Francesca Fati,Mariagrazia Fati,Emiliano Votta,Elena De Momi (1991). Optimizing Heart Valve Surgery with Model-Free Catheter Control.
  13. A Colorni,M Dorigo,V Maniezzo (1991). Figure 4: Initial conditions between ant colony in a nest and food source (Dorigo, Maniezzo & Colorni, 1996)..
  14. Anna Bicchi,Francesca Fati,Mariagrazia Fati,Emiliano Votta,Elena De Momi (1992). Optimizing Heart Valve Surgery with Model-Free Catheter Control.
  15. R Beckers,J Deneubourg,S Goss (1992). Trails and U-turns in the selection of a path by the ant Lasius niger.
  16. S Goss,S Aron,J Deneubourg,J Pasteels (1989). Self-organized shortcuts in the Argentine ant.
  17. (1990). Der Verlag von Julius Springer im Jahre 1912.
  18. A Waler,Elena Kosters,Marchiori,A Ard,Oerlemans (2004). Mining Clusters with Association July (1989), pp. browsing and summarization of large sets of Association Rules.
  19. Guichong Li,Howard Hamilton (2004). Basic Association Rules.
  20. W Li,J Han,J Pei (2001). CMAR: accurate and efficient classification based on multiple classassociation rules.
  21. A Thabtah,P Cowling (2007). A greedy classification algorithm based on association rule.
  22. Adriano Veloso,Wagner Meira,Marcos Gonçalves,Mohammed Zaki (2007). Multi-label Lazy Associative Classification.
  23. S Kannan,R Bhaskaran (2009). Rule Based Gujarati Morphological Analyzer.
  24. Xinqi Zheng,Lu Zhao (2008). Association Rule Analysis of Spatial Data Mining Based on Matlab-A Case of Ancheng Township in China.
  25. Moses Santhakumar (2003). Transportation system management for Madurai city using GIS.
  26. Aditi Pai,Deepika Khatri (2008). She buys to conquer.
  27. J Dunn (1974). Well-Separated Clusters and Optimal Fuzzy Partitions.
  28. H Toivonen,M Klemettinen,P Ronkainen,K Hatonen,H Mannila (1995). Pruning and grouping discovered association rules.
  29. Pi Dechang,Qin Xiaolin (2008). A New Fuzzy Clustering Algorithm on Association Rules for Knowledge Management.
  30. Jorge Alipio (1999). Hierarchical Clustering for thematic Rules.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. J.Arunadevi. 1970. \u201cA Two step optimized spatial Association rule Mining Algorithm by hybrid evolutionary algorithm and cluster segmentation.\u201d. Unknown Journal GJCST Volume 11 (GJCST Volume 11 Issue 12): .

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July 6, 2011

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en
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A novel two step approach by adopting hybrid evolutionary algorithm with cluster segmentation for Spatial Association Rule mining (SAR) is presented in this paper.Here first step concentrates on the optimization of SAR using the hybrid evolutionary algorithm which uses genetic algorithm and ant colony optimization (ACO). Multi objective genetic algorithm is used to provide the diversity of associations. ACO is performed to come out of local optima. In the second step, cluster the generated association rules used for the target group segmentation. Preferential based segmentation of the women of various groups belongs to the Madurai city, Tamilnadu, India. Here, number of rules generated by the first step of our SAR is minimized, also time generation for the rules are also minimized. Lift ratio increased for the generated rules.

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A Two step optimized spatial Association rule Mining Algorithm by hybrid evolutionary algorithm and cluster segmentation.

Dr. J.Arunadevi
Dr. J.Arunadevi Madurai Kamaraj University
Dr.V.Rajamani
Dr.V.Rajamani

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