The Journal of Machine Learning Research
ICML '06 Proceedings of the 23rd international conference on Machine learning
Topics over time: a non-Markov continuous-time model of topical trends
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Evolutionary spectral clustering by incorporating temporal smoothness
Proceedings of the 13th 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
The dynamic hierarchical Dirichlet process
Proceedings of the 25th international conference on Machine learning
Community evolution in dynamic multi-mode networks
Proceedings of the 14th 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
Robust Time-Referenced Segmentation of Moving Object Trajectories
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on 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
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Interactive, topic-based visual text summarization and analysis
Proceedings of the 18th ACM conference on Information and knowledge management
On-line evolutionary exponential family mixture
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents
IEEE Transactions on Pattern Analysis and Machine Intelligence
TIARA: a visual exploratory text analytic system
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Tracking trends: incorporating term volume into temporal topic models
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
A time-dependent topic model for multiple text streams
Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining
Accounting for data dependencies within a hierarchical dirichlet process mixture model
Proceedings of the 20th ACM international conference on Information and knowledge management
Supervised language modeling for temporal resolution of texts
Proceedings of the 20th ACM international conference on Information and knowledge management
Sequential Modeling of Topic Dynamics with Multiple Timescales
ACM Transactions on Knowledge Discovery from Data (TKDD)
Analyzing the flow of knowledge in computer mediated teams
Proceedings of the 2013 conference on Computer supported cooperative work
Transfer learning using a nonparametric sparse topic model
Neurocomputing
Mining evolutionary multi-branch trees from text streams
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Lead-lag analysis via sparse co-projection in correlated text streams
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Dynamic joint sentiment-topic model
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
Timeline generation: tracking individuals on twitter
Proceedings of the 23rd international conference on World wide web
Adaptive evolutionary clustering
Data Mining and Knowledge Discovery
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Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary hierarchical Dirichlet processes (EvoHDP) to discover interesting cluster evolution patterns from such text data. We formulate the EvoHDP as a series of hierarchical Dirichlet processes~(HDP) by adding time dependencies to the adjacent epochs, and propose a cascaded Gibbs sampling scheme to infer the model. This approach can discover different evolving patterns of clusters, including emergence, disappearance, evolution within a corpus and across different corpora. Experiments over synthetic and real-world multiple correlated time-varying data sets illustrate the effectiveness of EvoHDP on discovering cluster evolution patterns.