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data sparseness problem

Education Sst evalita2011 basile_pierpaolo

1. UNIBA: Super Sense Tagging at EVALITA 2011 Pierpaolo Basile [email protected] of Computer ScienceUniversity of Bari “A. Moro” (ITALY) EVALITA 2011, Rome,…

Documents 1IBM T.J. Waston CLSP, The Johns Hopkins University Using Random Forests Language Models in IBM...

n-gram Smoothing Smoothing: take out some probability mass from seen n-grams and distribute among unseen n-grams Over 10 different smoothing techniques were proposed in the…

Documents Exploration Stratigraphy 2nd Edition

A mu B nd R rate than those using zero-azimuth 3D SRME and �2� on-the- about multiple reflections in seismic data. Some of the more interest- ing papers appear in the…

Documents Random Forests for Language Modeling

What Is a Language Model? A probability distribution over word sequences Based on conditional probability distributions: probability of a word given its history (past words)…

Documents Using Random Forests Language Models in IBM RT-04 CTS

n-gram Smoothing Smoothing: take out some probability mass from seen n-grams and distribute among unseen n-grams Over 10 different smoothing techniques were proposed in the…

Documents 11/24/2006 CLSP, The Johns Hopkins University Random Forests for Language Modeling Peng Xu and...

What Is a Language Model? A probability distribution over word sequences Based on conditional probability distributions: probability of a word given its history (past words)…