Proving geometric algorithm non-solvability: An application of factoring polynomials
Journal of Symbolic Computation
Robust regression and outlier detection
Robust regression and outlier detection
Comments on 'Parallel Algorithms for Hierarchical Clustering and Cluster Validity'
IEEE Transactions on Pattern Analysis and Machine Intelligence
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Analysis and design of server informative WWW-sites
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
Adaptive Web sites: automatically synthesizing Web pages
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Web usage mining for Web site evaluation
Communications of the ACM
Measuring similarity of interests for clustering web-users
ADC '01 Proceedings of the 12th Australasian database conference
Clustering the Users of Large Web Sites into Communities
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Fast Randomized Algorithms for Robust Estimation of Location
TSDM '00 Proceedings of the First International Workshop on Temporal, Spatial, and Spatio-Temporal Data Mining-Revised Papers
K-Harmonic Means - A Spatial Clustering Algorithm with Boosting
TSDM '00 Proceedings of the First International Workshop on Temporal, Spatial, and Spatio-Temporal Data Mining-Revised Papers
Discovering Associations in Spatial Data - An Efficient Medoid Based Approach
PAKDD '98 Proceedings of the Second Pacific-Asia Conference on Research and Development in Knowledge Discovery and Data Mining
Robust Clustering of Large Geo-referenced Data Sets
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Mining Access Patterns Efficiently from Web Logs
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Scalable Hierarchical Clustering Method for Sequences of Categorical Values
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Collaborative Filtering by Personality Diagnosis: A Hybrid Memory and Model-Based Approach
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
STING: A Statistical Information Grid Approach to Spatial Data Mining
VLDB '97 Proceedings of the 23rd International Conference on Very Large Data Bases
Knowledge discovery from users Web-page navigation
RIDE '97 Proceedings of the 7th International Workshop on Research Issues in Data Engineering (RIDE '97) High Performance Database Management for Large-Scale Applications
Determining WWW User's Next Access and Its Application to Pre-fetching
ISCC '97 Proceedings of the 2nd IEEE Symposium on Computers and Communications (ISCC '97)
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Adaptive web sites: an AI challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
Clustering with a genetically optimized approach
IEEE Transactions on Evolutionary Computation
Non-crisp Clustering by Fast, Convergent, and Robust Algorithms
PKDD '01 Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery
A Monotonic On-Line Linear Algorithm for Hierarchical Agglomerative Classification
Information Technology and Management
Characterizing customer groups for an e-commerce website
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
Combining queueing networks and web usage mining techniques for web performance analysis
Proceedings of the 2005 ACM symposium on Applied computing
AntClust: ant clustering and web usage mining
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Online fuzzy medoid based clustering algorithms
Neurocomputing
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Clustering plays a central role in segmenting markets. The identification of categories of visitors to a Web-site is very useful towards improved Web applications. However, the large volume involved in mining visitation paths, demands efficient clustering algorithms that are also resistant to noise and outliers. Also, dissimilarity between visitation paths involves sophisticated evaluation and results in large dimension of attribute-vectors. We present a randomized, iterative algorithm (a la Expectation Maximization or k-means) but based on discrete medoids. We prove that our algorithm converges and that has subquadratic complexity. We compare to the implementation of the fastest version of matrix-based clustering for visitor paths and show that our algorithm outperforms dramatically matrix-based methods.