Cluster Analysis, K-Nearest Neighbour and Artificial Neural Network Applied to Credit Data to Classify Credit Applicants

The ubiquity of digital devices and Internet has formed a constantly connected online environment which led to the extensive adoption of e-commerce. However, the active participation of growing number of stakeholders intensifies the highly competitive landscape of the dynamic e-commerce market and the scarcity of trust in e-commerce business impede the generation of consistent sales growth. The obstruction necessitates the implementation of innovative marketing strategies to enhance the relationships with customers to develop customer loyalty. Therefore, a machine learning driven personalized marketing approach is proposed to facilitate the implementation of personalized marketing in which there are 2 significant sequential elements namely, the development of personalized marketing contents and delivery of the contents to prospective customers. Cluster analysis is employed to perform customer segmentation to discover customer segments due to the capability of the analysis to identify similarities in customer preferences in which the discovered customer segments are used to construct personalized marketing contents. In addition, artificial neural network is employed to predict prospective customers due to the capability of artificial neural network to comprehend complex relationships between customer demographics and buying behaviour in which the prediction facilitates the delivery of the constructed personalized marketing contents to potential repeat customer to optimize the marketing initiative. The combination of cluster analysis and artificial neural network empowers the construction of an efficacious marketing pipeline which enhances the competency of e-commerce businesses.

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Storm surge prediction using an artificial neural network model and cluster analysis

Natural Hazards ◽

10.1007/s11069-009-9396-x ◽

2009 ◽

Vol 51 (1) ◽

pp. 97-114 ◽

Cited By ~ 18

Author(s):

Sung Hyup You ◽

Jang-Won Seo

Keyword(s):

Neural Network ◽

Cluster Analysis ◽

Artificial Neural Network ◽

Storm Surge ◽

Network Model ◽

Neural Network Model ◽

Artificial Neural Network Model ◽

Artificial Neural ◽

And Cluster Analysis

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A Note on Comparison between Statistical Cluster and Neural Network Cluster

Recent Patents on Engineering ◽

10.2174/1872212112666180216161153 ◽

2019 ◽

Vol 13 (2) ◽

pp. 166-173

Author(s):

Jagdish Prasad ◽

Rahul Rajawat

Keyword(s):

Neural Network ◽

Cluster Analysis ◽

Artificial Neural Network ◽

Population Data ◽

Hierarchical Cluster ◽

Data Matrix ◽

Cluster Method ◽

Network Cluster ◽

Artificial Neural ◽

Data Reduction Technique

Background: Cluster analysis is a data reduction technique in rows of the data matrix. This technique is widely used in engineering, biology, society, pattern recognition, and image processing. Objective: In this paper, self organized map (SOM) using the artificial neural network and different statistical techniques of cluster analysis are used on Population data of 33 districts of Rajasthan with 9 variables for comparison purpose. Methods: The goal of this work is to identify the most suitable technique for clustering the data by using the artificial neural network and different statistical clustering techniques. We received all patents regarding artificial neural network and k-means cluster method. Conclusion: The k-means cluster analysis is found as good as Neural Network cluster analysis, whereas Hierarchical cluster analysis and two steps cluster analysis provide some variation from the neural network cluster analysis.

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