Validating fuzzy partitions obtained through c-shells clustering
Pattern Recognition Letters - Special issue on fuzzy set technology in pattern recognition
On a class of fuzzy c-numbers clustering procedures for fuzzy data
Fuzzy Sets and Systems
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Automatic subspace clustering of high dimensional data for data mining applications
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
OPTICS: ordering points to identify the clustering structure
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
ACM Computing Surveys (CSUR)
Partitioning-based clustering for Web document categorization
Decision Support Systems - Special issue on WITS '97
Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values
Data Mining and Knowledge Discovery
Unsupervised fuzzy clustering with multi-center clusters
Fuzzy Sets and Systems - Clustering and modeling
Exploiting hierarchical domain structure to compute similarity
ACM Transactions on Information Systems (TOIS)
SLIQ: A Fast Scalable Classifier for Data Mining
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
WaveCluster: A Multi-Resolution Clustering Approach for Very Large Spatial Databases
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
SPRINT: A Scalable Parallel Classifier for Data Mining
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
d-Clusters: Capturing Subspace Correlation in a Large Data Set
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
Selecting the right objective measure for association analysis
Information Systems - Knowledge discovery and data mining (KDD 2002)
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A hybrid sales forecasting system based on clustering and decision trees
Decision Support Systems
A multi-attribute, multi-weight clustering approach to managing ";e-mail overload"
Decision Support Systems
Customer-oriented catalog segmentation: effective solution approaches
Decision Support Systems
Hierarchical clustering of mixed data based on distance hierarchy
Information Sciences: an International Journal
Newspaper demand prediction and replacement model based on fuzzy clustering and rules
Information Sciences: an International Journal
Comparison of different strategies of utilizing fuzzy clustering in structure identification
Information Sciences: an International Journal
A cluster validity index for fuzzy clustering
Information Sciences: an International Journal
A clustering method to identify representative financial ratios
Information Sciences: an International Journal
On the J-divergence of intuitionistic fuzzy sets with its application to pattern recognition
Information Sciences: an International Journal
A currency crisis and its perception with fuzzy C-means
Information Sciences: an International Journal
A probabilistic heuristic for a computationally difficult set covering problem
Operations Research Letters
Getting insights from the voices of customers: Conversation mining at a contact center
Information Sciences: an International Journal
A shift of mind - Introducing a concept creation model
Information Sciences: an International Journal
Electronic Commerce Research and Applications
Debugging complex software systems by means of pathfinder networks
Information Sciences: an International Journal
Effective vaccination policies
Information Sciences: an International Journal
Discovering multi-label temporal patterns in sequence databases
Information Sciences: an International Journal
A tool for design pattern detection and software architecture reconstruction
Information Sciences: an International Journal
Pattern mining of cloned codes in software systems
Information Sciences: an International Journal
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There have been many approaches used to discover useful information patterns from databases, such as concept description, associations, sequential patterns, classification, clustering, and deviation detection. This paper proposes a new type of information pattern, called a typical pattern, which is a small subset of objects selected from a large dataset that provides a compact and suitable representation of the original dataset. The Typical Patterns Mining (TPM) algorithm is developed to mine typical patterns from databases. Extensive experiments are carried out using a real dataset to demonstrate the usefulness of typical patterns in practical situations. The experimental results indicate that TPM is a computationally efficient method and that typical patterns can provide a compact and suitable representation of the original dataset.