Computer
Computational experience on four algorithms for the hard clustering problem
Pattern Recognition Letters
In search of optimal clusters using genetic algorithms
Pattern Recognition Letters
Viewing the WEB as a marketplace: the case of small companies
Decision Support Systems - Special issue on electronic commerce
Integration of self-organizing feature map and K-means algorithm for market segmentation
Computers and Operations Research
A Triangulation Method for the Sequential Mapping of Points from N-Space to Two-Space
IEEE Transactions on Computers
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A recommender system using GA K-means clustering in an online shopping market
Expert Systems with Applications: An International Journal
Intelligent physician segmentation and management based on KDD approach
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Outlier identification and market segmentation using kernel-based clustering techniques
Expert Systems with Applications: An International Journal
Service-oriented Technology Roadmap (SoTRM) using patent map for R&D strategy of service industry
Expert Systems with Applications: An International Journal
Applying artificial immune system and ant algorithm in air-conditioner market segmentation
Expert Systems with Applications: An International Journal
An efficient approach for building customer profiles from business data
Expert Systems with Applications: An International Journal
Applying text and data mining techniques to forecasting the trend of petitions filed to e-People
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Intra-pulse modulation recognition of unknown radar emitter signals using support vector clustering
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Using the Taguchi method for effective market segmentation
Expert Systems with Applications: An International Journal
Using context to improve the effectiveness of segmentation and targeting in e-commerce
Expert Systems with Applications: An International Journal
Methodological triangulation using neural networks for business research
Advances in Artificial Neural Systems
Expert Systems with Applications: An International Journal
Behavior scoring model for coalition loyalty programs by using summary variables of transaction data
Expert Systems with Applications: An International Journal
Review: Soft computing applications in customer segmentation: State-of-art review and critique
Expert Systems with Applications: An International Journal
Hi-index | 12.07 |
This study is dedicated to proposing a novel two-stage method, which first uses Self-Organizing Feature Maps (SOM) neural network to determine the number of clusters and the starting point, and then uses genetic K-means algorithm to find the final solution. The results of simulated data via a Monte Carlo study show that the proposed method outperforms two other methods, K-means and SOM followed by K-means (Kuo, Ho & Hu, 2002a), based on both within-cluster variations (SSW) and the number of misclassification. In order to further demonstrate the proposed approach's capability, a real-world problem of the fright transport industry market segmentation is employed. A questionnaire is designed and surveyed, after which factor analysis extracts the factors from the questionnaire items as the basis of market segmentation. Then the proposed method is used to cluster the customers. The results also indicate that the proposed method is better than the other two methods