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COLING
2008
14 years 6 days ago
Using Hidden Markov Random Fields to Combine Distributional and Pattern-Based Word Clustering
Word clustering is a conventional and important NLP task, and the literature has suggested two kinds of approaches to this problem. One is based on the distributional similarity a...
Nobuhiro Kaji, Masaru Kitsuregawa
ICPR
2000
IEEE
14 years 3 months ago
Hidden Markov Random Field Based Approach for Off-Line Handwritten Chinese Character Recognition
This paper presents a Hidden Markov Mesh Random Field (HMMRF) based approach for off-line handwritten Chinese characters recognition using statistical observation sequences embedd...
Qing Wang, Rongchun Zhao, Zheru Chi, David Dagan F...
NAACL
2010
13 years 8 months ago
Dependency Tree-based Sentiment Classification using CRFs with Hidden Variables
In this paper, we present a dependency treebased method for sentiment classification of Japanese and English subjective sentences using conditional random fields with hidden varia...
Tetsuji Nakagawa, Kentaro Inui, Sadao Kurohashi
ICASSP
2010
IEEE
13 years 5 months ago
Unsupervised knowledge acquisition for Extracting Named Entities from speech
This paper presents a Named Entity Recognition (NER) method dedicated to process speech transcriptions. The main principle behind this method is to collect in an unsupervised way ...
Frédéric Béchet, Eric Charton
ICML
2004
IEEE
14 years 4 months ago
Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs
We introduce a new perceptron-based discriminative learning algorithm for labeling structured data such as sequences, trees, and graphs. Since it is fully kernelized and uses poin...
Hisashi Kashima, Yuta Tsuboi