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» Extractive summarization using a latent variable model
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ACL
2011
14 years 1 months ago
Semi-supervised latent variable models for sentence-level sentiment analysis
We derive two variants of a semi-supervised model for fine-grained sentiment analysis. Both models leverage abundant natural supervision in the form of review ratings, as well as...
Oscar Täckström, Ryan T. McDonald
ICASSP
2008
IEEE
15 years 4 months ago
A comparative study of probabilistic ranking models for spoken document summarization
The purpose of extractive document summarization is to automatically select a number of indicative sentences, passages, or paragraphs from the original document according to a tar...
Shih-Hsiang Lin, Yi-Ting Chen, Hsin-Min Wang, Bin ...
UAI
2008
14 years 11 months ago
On Identifying Total Effects in the Presence of Latent Variables and Selection bias
Assume that cause-effect relationships between variables can be described as a directed acyclic graph and the corresponding linear structural equation model We consider the identi...
Manabu Kuroki, Zhihong Cai
ICASSP
2011
IEEE
14 years 1 months ago
Improving melody extraction using Probabilistic Latent Component Analysis
We propose a new approach for automatic melody extraction from polyphonic audio, based on Probabilistic Latent Component Analysis (PLCA). An audio signal is first divided into vo...
Jinyu Han, Ching-Wei Chen
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COLING
2010
14 years 4 months ago
A Discriminative Latent Variable-Based "DE" Classifier for Chinese-English SMT
Syntactic reordering on the source-side is an effective way of handling word order differences. The (DE) construction is a flexible and ubiquitous syntactic structure in Chinese w...
Jinhua Du, Andy Way