Self-organization and associative memory: 3rd edition
Self-organization and associative memory: 3rd edition
CACTUS—clustering categorical data using summaries
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering transactions using large items
Proceedings of the eighth international conference on Information and knowledge management
Two-phase clustering process for outliers detection
Pattern Recognition Letters
COOLCAT: an entropy-based algorithm for categorical clustering
Proceedings of the eleventh international conference on Information and knowledge management
An iterative initial-points refinement algorithm for categorical data clustering
Pattern Recognition Letters
Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values
Data Mining and Knowledge Discovery
Squeezer: an efficient algorithm for clustering categorical data
Journal of Computer Science and Technology
PKDD '02 Proceedings of the 6th European Conference on Principles of Data Mining and Knowledge Discovery
Clustering Categorical Data: An Approach Based on Dynamical Systems
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
An Efficient Clustering Algorithm for Market Basket Data Based on Small Large Ratios
COMPSAC '01 Proceedings of the 25th International Computer Software and Applications Conference on Invigorating Software Development
Clustering Large Categorical Data
PAKDD '02 Proceedings of the 6th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Discovering cluster-based local outliers
Pattern Recognition Letters
CLOPE: a fast and effective clustering algorithm for transactional data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Caucus-based Transaction Clustering
DASFAA '03 Proceedings of the Eighth International Conference on Database Systems for Advanced Applications
A Self-Organizing Map with Expanding Force for Data Clustering and Visualization
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Using Category-Based Adherence to Cluster Market-Basket Data
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
ROCK: A Robust Clustering Algorithm for Categorical Attributes
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Clustering binary data streams with K-means
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
On the use of self-organizing maps for clustering and visualization
Intelligent Data Analysis
A fuzzy k-modes algorithm for clustering categorical data
IEEE Transactions on Fuzzy Systems
k-ANMI: A mutual information based clustering algorithm for categorical data
Information Fusion
G-ANMI: A mutual information based genetic clustering algorithm for categorical data
Knowledge-Based Systems
A self-organizing map for transactional data and the related categorical domain
Applied Soft Computing
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Self-Organizing Map (SOM) networks have been successfully applied as a clustering method to numeric datasets. However, it is not feasible to directly apply SOM for clustering transactional data. This paper proposes the Transactions Clustering using SOM (TCSOM) algorithm for clustering binary transactional data. In the TCSOM algorithm, a normalized Dot Product norm based dissimilarity measure is utilized for measuring the distance between input vector and output neuron. And a modified weight adaptation function is employed for adjusting weights of the winner and its neighbors. More importantly, TCSOM is a one-pass algorithm, which is extremely suitable for data mining applications. Experimental results on real datasets show that TCSOM algorithm is superior to those state-of-the-art transactional data clustering algorithms with respect to clustering accuracy.