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INTERSPEECH
2010
13 years 2 months ago
Extractive summarization using a latent variable model
Extractive multi-document summarization is the task of choosing sentences from a set of documents to compose a summary text in response to a user query. We propose a generative ap...
Asli Çelikyilmaz, Dilek Hakkani-Tür
JAIR
2007
151views more  JAIR 2007»
13 years 7 months ago
Topic and Role Discovery in Social Networks with Experiments on Enron and Academic Email
Previous work in social network analysis (SNA) has modeled the existence of links from one entity to another, but not the attributes such as language content or topics on those li...
Andrew McCallum, Xuerui Wang, Andrés Corrad...
ICDM
2008
IEEE
224views Data Mining» more  ICDM 2008»
14 years 2 months ago
A Non-parametric Approach to Pair-Wise Dynamic Topic Correlation Detection
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...
Yang Song, Lu Zhang 0007, C. Lee Giles
JCDL
2006
ACM
159views Education» more  JCDL 2006»
14 years 1 months ago
Bibliometric impact measures leveraging topic analysis
Measurements of the impact and history of research literature provide a useful complement to scientific digital library collections. Bibliometric indicators have been extensively...
Gideon S. Mann, David M. Mimno, Andrew McCallum
CVPR
2007
IEEE
14 years 9 months ago
A Topic-Motion Model for Unsupervised Video Object Discovery
The bag-of-words representation has attracted a lot of attention recently in the field of object recognition. Based on the bag-of-words representation, topic models such as Probab...
David Liu, Tsuhan Chen