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INTERSPEECH
2010
12 years 12 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
PRL
2008
181views more  PRL 2008»
13 years 5 months ago
Extractive spoken document summarization for information retrieval
The purpose of extractive summarization is to automatically select a number of indicative sentences, passages, or paragraphs from the original document according to a target summa...
Berlin Chen, Yi-Ting Chen
ICRA
2007
IEEE
189views Robotics» more  ICRA 2007»
13 years 11 months ago
Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
Georgios Petkos, Sethu Vijayakumar
SIGIR
2008
ACM
13 years 5 months ago
Latent dirichlet allocation based multi-document summarization
Extraction based Multi-Document Summarization Algorithms consist of choosing sentences from the documents using some weighting mechanism and combining them into a summary. In this...
Rachit Arora, Balaraman Ravindran
ACL
2010
13 years 3 months ago
A Hybrid Hierarchical Model for Multi-Document Summarization
Scoring sentences in documents given abstract summaries created by humans is important in extractive multi-document summarization. In this paper, we formulate extractive summariza...
Asli Çelikyilmaz, Dilek Hakkani-Tur