International Journal of
Computer Sciences and Engineering

Scholarly Peer-Reviewed, and Fully Refereed Scientific Research Journal
Analysis of Customer Behaviour using Modern Data Mining Techniques
Analysis of Customer Behaviour using Modern Data Mining Techniques
S.J. Nasti1 , M. Asgar2 , M.A. Butt3
1 Department of Computer Sciences, BGSB University, Rajouri, India.
2 School of Mathematical and Computer Sciences, BGSB University, Rajouri, India.
3 Department of Computer Sciences, University of Kashmir, Hazratbal, India.
Correspondence should be addressed to: samiah.mushtaq14@gmail.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-12 , Page no. 64-66, Dec-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i12.6466

Online published on Dec 31, 2017

Copyright © S.J. Nasti, M. Asgar, M.A. Butt . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 
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IEEE Style Citation: S.J. Nasti, M. Asgar, M.A. Butt , “Analysis of Customer Behaviour using Modern Data Mining Techniques”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.12, pp.64-66, 2017.

MLA Style Citation: S.J. Nasti, M. Asgar, M.A. Butt "Analysis of Customer Behaviour using Modern Data Mining Techniques." International Journal of Computer Sciences and Engineering 5.12 (2017): 64-66.

APA Style Citation: S.J. Nasti, M. Asgar, M.A. Butt , (2017). Analysis of Customer Behaviour using Modern Data Mining Techniques. International Journal of Computer Sciences and Engineering, 5(12), 64-66.
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Abstract :
As we know enormous amount of data is present on the Internet and in order to get value out of this data and present the information to the user in a very simple form, researchers are working hard to collate this data.This colossal size of data on Internet is the most important source for decision making and marketing now-a-days. The paper presents a proposed model to understand online customer’s buying behaviour based on decision tree and artificial neural network models.Our model is comparatively good at predicting the precision of customer’s buying behaviour.
Key-Words / Index Term :
Artificial Neural Network ,Buying Behaviour, Confusion Matrix, Data Mining, Decision Tree
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