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COLING
2008
13 years 8 months ago
Extractive Summarization Using Supervised and Semi-Supervised Learning
It is difficult to identify sentence importance from a single point of view. In this paper, we propose a learning-based approach to combine various sentence features. They are cat...
Kam-Fai Wong, Mingli Wu, Wenjie Li
ACL
2006
13 years 8 months ago
Trimming CFG Parse Trees for Sentence Compression Using Machine Learning Approaches
Sentence compression is a task of creating a short grammatical sentence by removing extraneous words or phrases from an original sentence while preserving its meaning. Existing me...
Yuya Unno, Takashi Ninomiya, Yusuke Miyao, Jun-ich...
ICASSP
2010
IEEE
13 years 7 months ago
Leveraging evaluation metric-related training criteria for speech summarization
Many of the existing machine-learning approaches to speech summarization cast important sentence selection as a two-class classification problem and have shown empirical success f...
Shih-Hsiang Lin, Yu-Mei Chang, Jia-Wen Liu, Berlin...
CORR
2012
Springer
183views Education» more  CORR 2012»
12 years 3 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
ACL
2010
13 years 5 months ago
Optimizing Informativeness and Readability for Sentiment Summarization
We propose a novel algorithm for sentiment summarization that takes account of informativeness and readability, simultaneously. Our algorithm generates a summary by selecting and ...
Hitoshi Nishikawa, Takaaki Hasegawa, Yoshihiro Mat...