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ICML
2010
IEEE
15 years 5 months ago
Heterogeneous Continuous Dynamic Bayesian Networks with Flexible Structure and Inter-Time Segment Information Sharing
Classical dynamic Bayesian networks (DBNs) are based on the homogeneous Markov assumption and cannot deal with heterogeneity and non-stationarity in temporal processes. Various ap...
Frank Dondelinger, Sophie Lebre, Dirk Husmeier
ICASSP
2008
IEEE
16 years 1 months ago
Rhetorical-State Hidden Markov Models for extractive speech summarization
We propose an extractive summarization system with a novel non-generative probabilistic framework for speech summarization. One of the most underutilized features in extractive su...
Pascale Fung, Ricky Ho Yin Chan, Justin Jian Zhang
ICML
2009
IEEE
16 years 1 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
WWW
2006
ACM
16 years 7 months ago
POLYPHONET: an advanced social network extraction system from the web
Social networks play important roles in the Semantic Web: knowledge management, information retrieval, ubiquitous computing, and so on. We propose a social network extraction syst...
Hideaki Takeda, Junichiro Mori, Kôiti Hasida...
CIKM
2009
Springer
16 years 1 months ago
The impact of document structure on keyphrase extraction
Keyphrases are short phrases that reflect the main topic of a document. Because manually annotating documents with keyphrases is a time-consuming process, several automatic appro...
Katja Hofmann, Manos Tsagkias, Edgar Meij, Maarten...