Reconstruction of rooted trees from subtrees
Discrete Applied Mathematics
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
A probabilistic framework for semi-supervised clustering
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Modeling word burstiness using the Dirichlet distribution
ICML '05 Proceedings of the 22nd international conference on Machine learning
Semi-Supervised Clustering with Metric Learning Using Relative Comparisons
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
ICML '06 Proceedings of the 23rd international conference on Machine learning
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining correlated bursty topic patterns from coordinated text streams
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining common topics from multiple asynchronous text streams
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Dirichlet Process Based Evolutionary Clustering
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Data Mining and Knowledge Discovery
Topic modeling for OLAP on multidimensional text databases: topic cube and its applications
Statistical Analysis and Data Mining - Best of SDM'09
Hierarchical Agglomerative Clustering with Ordering Constraints
WKDD '10 Proceedings of the 2010 Third International Conference on Knowledge Discovery and Data Mining
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Unified analysis of streaming news
Proceedings of the 20th international conference on World wide web
Clustering with relative constraints
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
TextFlow: Towards Better Understanding of Evolving Topics in Text
IEEE Transactions on Visualization and Computer Graphics
Semi-supervised Hierarchical Clustering
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
Tracking and Connecting Topics via Incremental Hierarchical Dirichlet Processes
ICDM '11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining
A Metric for Phylogenetic Trees Based on Matching
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Automatic taxonomy construction from keywords
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
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Understanding topic hierarchies in text streams and their evolution patterns over time is very important in many applications. In this paper, we propose an evolutionary multi-branch tree clustering method for streaming text data. We build evolutionary trees in a Bayesian online filtering framework. The tree construction is formulated as an online posterior estimation problem, which considers both the likelihood of the current tree and conditional prior given the previous tree. We also introduce a constraint model to compute the conditional prior of a tree in the multi-branch setting. Experiments on real world news data demonstrate that our algorithm can better incorporate historical tree information and is more efficient and effective than the traditional evolutionary hierarchical clustering algorithm.