Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Journal of Computational and Applied Mathematics
ACM Computing Surveys (CSUR)
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A clustering algorithm based on graph connectivity
Information Processing Letters
On Clustering Validation Techniques
Journal of Intelligent Information Systems
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
A Min-max Cut Algorithm for Graph Partitioning and Data Clustering
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
A Web page prediction model based on click-stream tree representation of user behavior
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
A New Graph-Based Evolutionary Approach to Sequence Clustering
ICMLA '05 Proceedings of the Fourth International Conference on Machine Learning and Applications
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Cluster Analysis
Exploiting the trade-off — the benefits of multiple objectives in data clustering
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
Biological cluster validity indices based on the gene ontology
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
An Evolutionary Approach to Multiobjective Clustering
IEEE Transactions on Evolutionary Computation
News Recommender System Based on Topic Detection and Tracking
RSKT '09 Proceedings of the 4th International Conference on Rough Sets and Knowledge Technology
Evolutionary image segmentation based on multiobjective clustering
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Multiobjective evolutionary algorithms for dynamic social network clustering
Proceedings of the 12th annual conference on Genetic and evolutionary computation
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In web recommender systems, clustering is done offline to extract usage patterns and a successful recommendation highly depends on the quality of this clustering solution. In these types of applications, data to be clustered is in the form of user sessions which are sequences of web pages visited by the user. Sequence clustering is one of the important tools to work with this type of data. One way to represent sequence data is through weighted, undirected graphs where each sequence is a vertex and the pairwise similarities between the user sessions are the edges. Through this representation, the problem becomes equivalent to graph partitioning which is NP-complete and is best approached using multiple objectives. Hence it is suitable to use multiobjective evolutionary algorithms (MOEA) to solve it. The main focus of this paper is to determine an effective MOEA to cluster sequence data. Several existing approaches in literature are compared on sample data sets and the most suitable approach is determined.