Algorithms for clustering data
Algorithms for clustering data
Static and dynamic information organization with star clusters
Proceedings of the seventh international conference on Information and knowledge management
Web document clustering: a feasibility demonstration
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Fast and effective text mining using linear-time document clustering
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Evaluation of hierarchical clustering algorithms for document datasets
Proceedings of the eleventh international conference on Information and knowledge management
Frequent term-based text clustering
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
An Incremental Approach to Building a Cluster Hierarchy
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Hierarchical Clustering Algorithms for Document Datasets
Data Mining and Knowledge Discovery
A General Framework for Agglomerative Hierarchical Clustering Algorithms
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
High Quality, Efficient Hierarchical Document Clustering Using Closed Interesting Itemsets
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Text document clustering based on frequent word meaning sequences
Data & Knowledge Engineering
A comparison of extrinsic clustering evaluation metrics based on formal constraints
Information Retrieval
Phrase-based hierarchical clustering of web search results
ECIR'03 Proceedings of the 25th European conference on IR research
Improving the dynamic hierarchical compact clustering algorithm by using feature selection
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
Hierarchical confidence-based active clustering
Proceedings of the 27th Annual ACM Symposium on Applied Computing
In search of optimal centroids on data clustering using a binary search algorithm
Pattern Recognition Letters
A new overlapping clustering algorithm based on graph theory
MICAI'12 Proceedings of the 11th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Probability-based text clustering algorithm by alternately repeating two operations
Journal of Information Science
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In this paper, two clustering algorithms called dynamic hierarchical compact and dynamic hierarchical star are presented. Both methods aim to construct a cluster hierarchy, dealing with dynamic data sets. The first creates disjoint hierarchies of clusters, while the second obtains overlapped hierarchies. The experimental results on several benchmark text collections show that these methods not only are suitable for producing hierarchical clustering solutions in dynamic environments effectively and efficiently, but also offer hierarchies easier to browse than traditional algorithms. Therefore, we advocate its use for tasks that require dynamic clustering, such as information organization, creation of document taxonomies and hierarchical topic detection.