Authors:
Indu Chhabra,Gunmala Suri,DOI NO:
https://doi.org/10.26782/jmcms.2019.04.00014Keywords:
Customer behavior analysis, Data mining, Intellectual Management,Neural Networks,Genetic algorithm,Retail industry,Abstract
Current trends in software development have shown a strong move towards autonomous and rational mechanism for the human societal growth. Customer behavior analysis and its knowledge have always been given its due importance in research community to develop real life practical solutions. In this scenario a real-world phenomenon of customer buying habits is tested through observations lying in the database and is experimented and validated through association mining. On the flip side of the coin, the development of intellectual and evolutionary data mining tool for retail industries through the machine learning algorithm has always been proved to adequately respond to environment changes and improve its behavioral rules to derive intelligent quotient. A case study of Market basket analysis is simulated to imitate customer behavior in the dynamic environment to predict about rational and intelligent behavior for future business expansion.Refference:
I.Ahmed, S.R.,”Applications of data mining in retail business”, Information Technology: Coding andComputing,vol. 2, 2004, pp.455-459.
II.AmandeepKaur, P.S.Grover, “Performance Efficiency Assessment for Software Systems” a chapter in “Advances in Intelligent Systems and Computing”book series, AISC, Volume 731, June 2018.
III.Ansari Azarnoush and Riasi Arash, “Customer Clustering Using a Combination of Fuzzy C-Means and Genetic Algorithms”, International Journal of Business and Management; vol. 11, Canadian Center of Science and Education, June 2016, ISSN 1833-3850.
IV.Ismail, J., “The design of an e-Learning System: Beyond the hype”, Internet and Higher Education, vol. 4, 2002.
V.Ngai, E.W.T, Xiu, Li and Chau, D.C.K.,“Application of data mining techniques in customer relationship management: A literature review and classification”, Expert systems with applications, vol. 36,March 2009, pp. 2592-2602.
VI.Pillai Jyothi, “User centric approach to itemset utility mining in Market Basket Analysis”, International Journal on Computer Science and Engineering, Jan 2011.
VII.Sandhu Parvinder, Dalvinder S. and Panda S. N ,“Mining utility-oriented association rules: An efficient approach based on profit and quantity”, International Journal of the Physical Sciences,vol. 6, pp. 301-307, Jan 2011.
VIII.Vijaylakshmi S., Mohan V., Suresh Raja S., “Mining of users’ access behavior for frequent sequential pattern from web logs”, International Journal of Database Management System (IJDM), vol. 2, August 2010.
IX.Woo,J.Y.,Bae,S.M., andPark, S.C., “Visualization method for customer targeting using customer map”, Expert Systems with Applications,vol.28, 2005, pp.763-772.
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