%0 Conference Paper %1 li2006 %A Li, Wei %A Wang, Xuerui %A McCallum, Andrew %B Proceedings of the 2006 AAAI Workshop on EventExtractionand Synthesis %D 2006 %K topic_tracking %P 48--53 %T A Continuous-Time Model of Topic Co-occurrence Trends %U http://www.aaai.org/Papers/Workshops/2006/WS-06-07/WS06-07-010.pdf %X 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.

@inproceedings{li2006, abstract = {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.}, added-at = {2009-10-22T15:19:45.000+0200}, author = {Li, Wei and Wang, Xuerui and McCallum, Andrew}, biburl = {https://www.bibsonomy.org/bibtex/2adb595a45889f4bc65e9af5ed3d8c985/jnothman}, booktitle = {Proceedings of the 2006 AAAI Workshop on EventExtractionand Synthesis}, description = {Combines own Topics Over Time (TOT) and Pachinko Allocation Model (PAM) to capture topic correlations over time. Handles topic hierarchies.}, interhash = {4c468ef4ed5d1b8bfba69fa86b32d7fb}, intrahash = {adb595a45889f4bc65e9af5ed3d8c985}, keywords = {topic_tracking}, pages = {48--53}, timestamp = {2009-10-22T15:19:45.000+0200}, title = {A Continuous-Time Model of Topic Co-occurrence Trends}, url = {http://www.aaai.org/Papers/Workshops/2006/WS-06-07/WS06-07-010.pdf}, year = 2006 }