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» Detecting Topic Drift with Compound Topic Models
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ICWSM
2009
13 years 3 months ago
Detecting Topic Drift with Compound Topic Models
Dan Knights, Michael C. Mozer, Nicolas Nicolov
ICML
2010
IEEE
13 years 6 months ago
The IBP Compound Dirichlet Process and its Application to Focused Topic Modeling
The hierarchical Dirichlet process (HDP) is a Bayesian nonparametric mixed membership model--each data point is modeled with a collection of components of different proportions. T...
Sinead Williamson, Chong Wang, Katherine A. Heller...
COLING
2002
13 years 5 months ago
NLP and IR Approaches to Monolingual and Multilingual Link Detection
This paper considers several important issues for monolingual and multilingual link detection. The experimental results show that nouns, verbs, adjectives and compound nouns are u...
Ying-Ju Chen, Hsin-Hsi Chen
NAACL
2004
13 years 6 months ago
Catching the Drift: Probabilistic Content Models, with Applications to Generation and Summarization
We consider the problem of modeling the content structure of texts within a specific domain, in terms of the topics the texts address and the order in which these topics appear. W...
Regina Barzilay, Lillian Lee
SBP
2011
Springer
13 years 7 days ago
Identifying Health-Related Topics on Twitter - An Exploration of Tobacco-Related Tweets as a Test Topic
Public health-related topics are difficult to identify in large conversational datasets like Twitter. This study examines how to model and discover public health topics and themes ...
Kyle W. Prier, Matthew S. Smith, Christophe G. Gir...