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» Extractive summarization using a latent variable model
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MCS
2004
Springer
14 years 1 months ago
A Probabilistic Model Using Information Theoretic Measures for Cluster Ensembles
Abstract. This paper presents a probabilistic model for combining cluster ensembles utilizing information theoretic measures. Starting from a co-association matrix which summarizes...
Hanan Ayad, Otman A. Basir, Mohamed Kamel
KCAP
2005
ACM
14 years 1 months ago
AutoFeed: an unsupervised learning system for generating webfeeds
The AutoFeed system automatically extracts data from semistructured web sites. Previously, researchers have developed two types of supervised learning approaches for extracting we...
Bora Gazen, Steven Minton
JMLR
2008
188views more  JMLR 2008»
13 years 7 months ago
Maximal Causes for Non-linear Component Extraction
We study a generative model in which hidden causes combine competitively to produce observations. Multiple active causes combine to determine the value of an observed variable thr...
Jörg Lücke, Maneesh Sahani
CIKM
2010
Springer
13 years 6 months ago
Collaborative Dual-PLSA: mining distinction and commonality across multiple domains for text classification
:  Collaborative Dual-PLSA: Mining Distinction and Commonality across Multiple Domains for Text Classification Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhon...
Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yu...
ECCV
2006
Springer
14 years 9 months ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn