2010 EvolutionaryHierarchicalDirichl

• (Zhang et al., 2010) ⇒ Jianwen Zhang, Yangqiu Song, Changshui Zhang, and Shixia Liu. (2010). “Evolutionary Hierarchical Dirichlet Processes for Multiple Correlated Time-varying Corpora.” In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2010). doi:10.1145/1835804.1835940

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%22Evolutionary+hierarchical+dirichlet+processes+for+multiple+correlated+time-varying+corpora%22+2010
• http://portal.acm.org/citation.cfm?id=1835940&preflayout=flat#citedby

Quotes

Abstract

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.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2010 EvolutionaryHierarchicalDirichl	Changshui Zhang Shixia Liu Yangqiu Song Jianwen Zhang			Evolutionary Hierarchical Dirichlet Processes for Multiple Correlated Time-varying Corpora		KDD-2010 Proceedings	http://research.microsoft.com/en-us/um/people/shliu/p1079-zhang.pdf	10.1145/1835804.1835940		2010