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» Extractive summarization using a latent variable model
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ACL
2011
12 years 10 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
14 years 1 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
13 years 8 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
12 years 10 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
COLING
2010
13 years 1 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