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International Journal on Computational Science & Applications
(IJCSA)
ISSN : 2200-0011
https://wireilla.com/ijcsa/index.html
Current Issue : April 2019, Volume 9, Number 1/2---
Table of Contents
https://wireilla.com/ijcsa/vol9.html
Paper - 01
A NEW EXTRACTION OPTIMIZATION APPROACH TO
FREQUENT 2 ITEM SETS
Nombre Claude Issa1
, Brou Konan Marcellin2
, Kimou Kouadio Prosper3
1
Polytechnic Doctoral School, 2
National Polytechnic Institute Houphouet Boigny –
Yamoussoukro and 3
Research Laboratory of Computer Science and Technology
ABSTRACT
In this paper, we propose a new optimization approach to the APRIORI reference algorithm
(AGR 94) for 2-itemsets (sets of cardinal 2). The approach used is based on two-item sets. We
start by calculating the 1- itemets supports (cardinal 1 sets), then we prune the 1-itemsets not
frequent and keep only those that are frequent (ie those with the item sets whose values are
greater than or equal to a fixed minimum threshold). During the second iteration, we sort the
frequent 1-itemsets in descending order of their respective supports and then we form the 2-
itemsets. In this way the rules of association are discovered more quickly. Experimentally, the
comparison of our algorithm OPTI2I with APRIORI, PASCAL, CLOSE and MAXMINER,
shows its efficiency on weakly correlated data. Our work has also led to a classical model of
sideby-side classification of items that we have obtained by establishing a relationship between
the different sets of 2-itemsets.
KEYWORDS
Optimization, Frequent Itemsets, Association Rules, Low-Correlation Data, Supports
For More Details: https://wireilla.com/papers/ijcsa/V9N2/9219ijcsa01.pdf
Volume Link: https://wireilla.com/ijcsa/fulltext/9219ijcsa01.html
REFERENCES
[1] R. Agrawal, R. Srikant, H, "Fast algorithms for mining association rules in large
databases",Research Report RJ 9839, IBM Almaden Research Center, San Jose, California,June
1994.
[2] J. Azé. Extraction of knowledge from digital and textual data. Ph.D. thesis, Paris-Sud University,
december 2003.
[3] C.-C. Yu and Y.-L. Chen: Mining sequential patterns from multidimensional sequence data. IEEE
Transactions on Knowledge and Data Engineering, 17 (1): 136-140, 2005.
[4] Martine CADOT. Extract and validate complex relationships in human sciences: statistics, reasons
and rules of association, PhD thesis of the University of Franche-Comté - Besançon December
12,2006.
[5] G. Dong Z. Xing, J. Pei and P. Yu Yu: Mining Sequence Classifiers for Early Prediction. In
Proceedings of the 2008 SIAM International Conference on Data Mining (SDM'08), Atlanta,
GA,April 24-26, 2008.
[6] Ming-Chang Lee. Data mining - R - association rules and apriori algorithm 29 March 2009 [7] Yves
Bastide et al. Pascal: an algorithm for extracting frequent motifs, Ph.D. article, IRISA-INRIA -35042
Rennes Cedex, April 26, 2010.
[8] M Ramakrishna Murty, Murthy JVR, Prasada Reddy PVGD, Suresh Satapathy, "International
Information Systems Design and Intelligent Application-2012, Springer-AISC" (indexed
bySCOPUS) etc.), ISBN 978- 3-642-27443-5, Vol: 132, 2012, PP: 445-454. "
[9] Sadok Ben Yahia-Engelbert Mephu Nguifo. Association rule extraction approaches based on Galois
matching. Lens Computer Research Center - IUT de Lens University Street SP 16, F-62307
Lenscedex
[10] Thierry Lecroq. Extraction of rules of association, University of Rouen France N. Pasquier Y.
Bastide R. Taouil and L. Lakhal. Pruning closed items and lattices for association rules - 2016.
[11] Mostafa El Habib Daho and Al..Dynamic Pruning for Tree-based Ensembles. Pages 261. Year 2016.
[12] Professor Brou Konan Marcellin. Course material entitled "Chapter 2: Rules of Association"
INPHB, 2015 - 2016.
[13] Abdel-Basset, M., El-Shahat, D. and Mirjalili, S. (2018). A hybrid whale optimization algorithm
based on a local search strategy for the permutation flow store scheduling problem. Future
Generation Computer Systems, 85, 129-145.
[14] Abdel-Basset, M., M., G., Abdel-Fatah, L., and Mirjalili, S. (2018). An improved meta-heuristic
algorithm inspired by nature for 1-D bin packing problems. Personal and ubiquitous computing, 1-
16.
[15] Abdel-Basset, M., M., G., A. Gamal and F. Smarandache (2018). A hybrid approach of neutrosophic
sets and the DEMATEL method to develop supplier selection criteria. Automation of design for
embedded systems, 1-22.
[16] M., G, M., Mohamed, M., and Smarandache, F. A new method to solve the problems of linear
neutrino programming. Neural computation and applications, 1-11.
[17] M., M., G., Fakhry, A.E. and El-Henawy, I. (2018). 2 levels of grouping strategy to detect and locate
copy transfer forgery in digital images. Multimedia Tools and Applications, 1-19.
[18] Abdel M., & Mohamed, M. (2018). Internet of Things (IoT) and its impact on the supply chain: a
framework for creating intelligent, secure and efficient systems. Next-generation computer systems.
[19] Basset, M., G. Manogaran, M. Mohamed, and Rushdy, E. Internet of Things in an Intelligent
Educational Environment: Supporting Framework in the Decision-Making Process. Competition and
calculation: practice and experience, e4515.
[20] Abdel, M., M., G., Rashad, H., and Zaied, A.N.H. (2018). A comprehensive review of the quadratic
assignment problem: variants, hybrids, and applications. Journal of Ambient Intelligence and
Humanized Computing, 1-24.
[21] Ab, M., G, M., Mohamed, M. and Chilamkurti, N. (2018). Three-way decisions based on
neutrosophic sets and the AHP-QFD framework for the supplier selection problem. Next-generation
computer systems.

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New Optimization Approach for Frequent 2-Item Sets

  • 1. International Journal on Computational Science & Applications (IJCSA) ISSN : 2200-0011 https://wireilla.com/ijcsa/index.html Current Issue : April 2019, Volume 9, Number 1/2--- Table of Contents https://wireilla.com/ijcsa/vol9.html
  • 2. Paper - 01 A NEW EXTRACTION OPTIMIZATION APPROACH TO FREQUENT 2 ITEM SETS Nombre Claude Issa1 , Brou Konan Marcellin2 , Kimou Kouadio Prosper3 1 Polytechnic Doctoral School, 2 National Polytechnic Institute Houphouet Boigny – Yamoussoukro and 3 Research Laboratory of Computer Science and Technology ABSTRACT In this paper, we propose a new optimization approach to the APRIORI reference algorithm (AGR 94) for 2-itemsets (sets of cardinal 2). The approach used is based on two-item sets. We start by calculating the 1- itemets supports (cardinal 1 sets), then we prune the 1-itemsets not frequent and keep only those that are frequent (ie those with the item sets whose values are greater than or equal to a fixed minimum threshold). During the second iteration, we sort the frequent 1-itemsets in descending order of their respective supports and then we form the 2- itemsets. In this way the rules of association are discovered more quickly. Experimentally, the comparison of our algorithm OPTI2I with APRIORI, PASCAL, CLOSE and MAXMINER, shows its efficiency on weakly correlated data. Our work has also led to a classical model of sideby-side classification of items that we have obtained by establishing a relationship between the different sets of 2-itemsets. KEYWORDS Optimization, Frequent Itemsets, Association Rules, Low-Correlation Data, Supports For More Details: https://wireilla.com/papers/ijcsa/V9N2/9219ijcsa01.pdf Volume Link: https://wireilla.com/ijcsa/fulltext/9219ijcsa01.html
  • 3. REFERENCES [1] R. Agrawal, R. Srikant, H, "Fast algorithms for mining association rules in large databases",Research Report RJ 9839, IBM Almaden Research Center, San Jose, California,June 1994. [2] J. Azé. Extraction of knowledge from digital and textual data. Ph.D. thesis, Paris-Sud University, december 2003. [3] C.-C. Yu and Y.-L. Chen: Mining sequential patterns from multidimensional sequence data. IEEE Transactions on Knowledge and Data Engineering, 17 (1): 136-140, 2005. [4] Martine CADOT. Extract and validate complex relationships in human sciences: statistics, reasons and rules of association, PhD thesis of the University of Franche-Comté - Besançon December 12,2006. [5] G. Dong Z. Xing, J. Pei and P. Yu Yu: Mining Sequence Classifiers for Early Prediction. In Proceedings of the 2008 SIAM International Conference on Data Mining (SDM'08), Atlanta, GA,April 24-26, 2008. [6] Ming-Chang Lee. Data mining - R - association rules and apriori algorithm 29 March 2009 [7] Yves Bastide et al. Pascal: an algorithm for extracting frequent motifs, Ph.D. article, IRISA-INRIA -35042 Rennes Cedex, April 26, 2010. [8] M Ramakrishna Murty, Murthy JVR, Prasada Reddy PVGD, Suresh Satapathy, "International Information Systems Design and Intelligent Application-2012, Springer-AISC" (indexed bySCOPUS) etc.), ISBN 978- 3-642-27443-5, Vol: 132, 2012, PP: 445-454. " [9] Sadok Ben Yahia-Engelbert Mephu Nguifo. Association rule extraction approaches based on Galois matching. Lens Computer Research Center - IUT de Lens University Street SP 16, F-62307 Lenscedex [10] Thierry Lecroq. Extraction of rules of association, University of Rouen France N. Pasquier Y. Bastide R. Taouil and L. Lakhal. Pruning closed items and lattices for association rules - 2016. [11] Mostafa El Habib Daho and Al..Dynamic Pruning for Tree-based Ensembles. Pages 261. Year 2016. [12] Professor Brou Konan Marcellin. Course material entitled "Chapter 2: Rules of Association" INPHB, 2015 - 2016. [13] Abdel-Basset, M., El-Shahat, D. and Mirjalili, S. (2018). A hybrid whale optimization algorithm based on a local search strategy for the permutation flow store scheduling problem. Future Generation Computer Systems, 85, 129-145. [14] Abdel-Basset, M., M., G., Abdel-Fatah, L., and Mirjalili, S. (2018). An improved meta-heuristic algorithm inspired by nature for 1-D bin packing problems. Personal and ubiquitous computing, 1- 16.
  • 4. [15] Abdel-Basset, M., M., G., A. Gamal and F. Smarandache (2018). A hybrid approach of neutrosophic sets and the DEMATEL method to develop supplier selection criteria. Automation of design for embedded systems, 1-22. [16] M., G, M., Mohamed, M., and Smarandache, F. A new method to solve the problems of linear neutrino programming. Neural computation and applications, 1-11. [17] M., M., G., Fakhry, A.E. and El-Henawy, I. (2018). 2 levels of grouping strategy to detect and locate copy transfer forgery in digital images. Multimedia Tools and Applications, 1-19. [18] Abdel M., & Mohamed, M. (2018). Internet of Things (IoT) and its impact on the supply chain: a framework for creating intelligent, secure and efficient systems. Next-generation computer systems. [19] Basset, M., G. Manogaran, M. Mohamed, and Rushdy, E. Internet of Things in an Intelligent Educational Environment: Supporting Framework in the Decision-Making Process. Competition and calculation: practice and experience, e4515. [20] Abdel, M., M., G., Rashad, H., and Zaied, A.N.H. (2018). A comprehensive review of the quadratic assignment problem: variants, hybrids, and applications. Journal of Ambient Intelligence and Humanized Computing, 1-24. [21] Ab, M., G, M., Mohamed, M. and Chilamkurti, N. (2018). Three-way decisions based on neutrosophic sets and the AHP-QFD framework for the supplier selection problem. Next-generation computer systems.