A near-optimal initial seed value selection in K-means algorithm using a genetic algorithm
Pattern Recognition Letters
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
In search of optimal clusters using genetic algorithms
Pattern Recognition Letters
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Combining collaborative filtering with personal agents for better recommendations
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
An empirical comparison of four initialization methods for the K-Means algorithm
Pattern Recognition Letters
A Framework for Collaborative, Content-Based and Demographic Filtering
Artificial Intelligence Review - Special issue on data mining on the Internet
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Genetic Algorithms and Investment Strategies
Genetic Algorithms and Investment Strategies
Refining Initial Points for K-Means Clustering
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
Toward Global Optimization of Case-Based Reasoning Systems for Financial Forecasting
Applied Intelligence
Expert Systems with Applications: An International Journal
Welfare interface implementation using multiple facial features tracking for the disabled people
Pattern Recognition Letters
Recommendation in Education Portal by Relation Based Importance Ranking
ICWL '08 Proceedings of the 7th international conference on Advances in Web Based Learning
An entropy clustering analysis based on genetic algorithm
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Fuzzy theory and technology with applications
Mining tourist imagery to construct destination image position model
Expert Systems with Applications: An International Journal
Web-Based Recommender Systems and User Needs --the Comprehensive View
Proceedings of the 2008 conference on New Trends in Multimedia and Network Information Systems
Data spread-based entropy clustering method using adaptive learning
Expert Systems with Applications: An International Journal
MUADDIB: A distributed recommender system supporting device adaptivity
ACM Transactions on Information Systems (TOIS)
A hybrid approach for supplier cluster analysis
Computers & Mathematics with Applications
3PRS: a personalized popular program recommendation system for digital TV for P2P social networks
Multimedia Tools and Applications
Combinations of case-based reasoning with other intelligent methods
International Journal of Hybrid Intelligent Systems - CIMA-08
Genetic algorithm-based high-dimensional data clustering technique
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Clustering Indian stock market data for portfolio management
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
Improving the scalability of recommender systems by clustering using genetic algorithms
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part I
CPRS: A cloud-based program recommendation system for digital TV platforms
Future Generation Computer Systems
CPRS: a cloud-based program recommendation system for digital TV platforms
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Cluster ensembles in collaborative filtering recommendation
Applied Soft Computing
Expert Systems with Applications: An International Journal
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
In search of optimal centroids on data clustering using a binary search algorithm
Pattern Recognition Letters
A hybrid recommendation approach for a tourism system
Expert Systems with Applications: An International Journal
A topic-based recommender system for electronic marketplace platforms
Expert Systems with Applications: An International Journal
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Review: Soft computing applications in customer segmentation: State-of-art review and critique
Expert Systems with Applications: An International Journal
An Efficient Hybrid Artificial Bee Colony Algorithm for Customer Segmentation in Mobile E-commerce
Journal of Electronic Commerce in Organizations
A cloud-based intelligent TV program recommendation system
Computers and Electrical Engineering
Category role aided market segmentation approach to convenience store chain category management
Decision Support Systems
Hi-index | 12.06 |
The Internet is emerging as a new marketing channel, so understanding the characteristics of online customers' needs and expectations is considered a prerequisite for activating the consumer-oriented electronic commerce market. In this study, we propose a novel clustering algorithm based on genetic algorithms (GAs) to effectively segment the online shopping market. In general, GAs are believed to be effective on NP-complete global optimization problems, and they can provide good near-optimal solutions in reasonable time. Thus, we believe that a clustering technique with GA can provide a way of finding the relevant clusters more effectively. The research in this paper applied K-means clustering whose initial seeds are optimized by GA, which is called GA K-means, to a real-world online shopping market segmentation case. In this study, we compared the results of GA K-means to those of a simple K-means algorithm and self-organizing maps (SOM). The results showed that GA K-means clustering may improve segmentation performance in comparison to other typical clustering algorithms. In addition, our study validated the usefulness of the proposed model as a preprocessing tool for recommendation systems.