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Unpublished Paper
A Continuous-Time Model of Topic Co-occurrence Trends
  • Wei Li
  • Xuerui Wang
  • Andrew McCallum, University of Massachusetts - Amherst
Recent work in statistical topic models has investigated richer structures to capture either temporal or inter-topic correlations. This paper introduces a topic model that combines the advantages of two recently proposed models: (1) The Pachinko Allocation model (PAM), which captures arbitrary topic correlations with a directed acyclic graph (DAG), and (2) the Topics over Time model (TOT), which captures time-localized shifts in topic prevalence with a continuous distribution over timestamps. Our model can thus capture not only temporal patterns in individual topics, but also the temporal patterns in their co-occurrences. We present results on a research paper corpus, showing interesting correlations among topics and their changes over time.
Publication Date
This is the pre-published version harvested from CIIR.
Citation Information
Wei Li, Xuerui Wang and Andrew McCallum. "A Continuous-Time Model of Topic Co-occurrence Trends" (2006)
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