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» Name Tagging with Word Clusters and Discriminative Training
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NAACL
2004
13 years 6 months ago
Name Tagging with Word Clusters and Discriminative Training
We present a technique for augmenting annotated training data with hierarchical word clusters that are automatically derived from a large unannotated corpus. Cluster membership is...
Scott Miller, Jethran Guinness, Alex Zamanian
AAAI
2004
13 years 6 months ago
Discriminating Among Word Meanings by Identifying Similar Contexts
Word sense discrimination is an unsupervised clustering problem, which seeks to discover which instances of a word/s are used in the same meaning. This is done strictly based on i...
Amruta Purandare, Ted Pedersen
EMNLP
2004
13 years 6 months ago
Trained Named Entity Recognition using Distributional Clusters
This work applies boosted wrapper induction (BWI), a machine learning algorithm for information extraction from semi-structured documents, to the problem of named entity recogniti...
Dayne Freitag
ICPR
2008
IEEE
13 years 11 months ago
Discriminative HMM training with GA for handwritten word recognition
This paper presents a recognition system for isolated handwritten Bangla words, with a fixed lexicon, using a left-right Hidden Markov Model (HMM). A stochastic search method, nam...
Tapan Kumar Bhowmik, Swapan K. Parui, Utpal Roy
ICASSP
2011
IEEE
12 years 8 months ago
Named entity recognition from Conversational Telephone Speech leveraging Word Confusion Networks for training and recognition
Named Entity (NE) recognition from the results of Automatic Speech Recognition (ASR) is challenging because of ASR errors. To detect NEs, one of the options is to use a statistica...
Gakuto Kurata, Nobuyasu Itoh, Masafumi Nishimura, ...