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LREC
2008
93views Education» more  LREC 2008»
13 years 6 months ago
Using a Probabilistic Model of Context to Detect Word Obfuscation
This paper proposes a distributional model of word use and word meaning which is derived purely from a body of text, and then applies this model to determine whether certain words...
Sanaz Jabbari, Ben Allison, Louise Guthrie
ACL
2010
13 years 2 months ago
Topic Models for Word Sense Disambiguation and Token-Based Idiom Detection
This paper presents a probabilistic model for sense disambiguation which chooses the best sense based on the conditional probability of sense paraphrases given a context. We use a...
Linlin Li, Benjamin Roth, Caroline Sporleder
JCST
2010
153views more  JCST 2010»
12 years 11 months ago
Model Failure and Context Switching Using Logic-Based Stochastic Models
Abstract We define a notion of context that represents invariant, stable-over-time behavior in an environment and we propose an algorithm for detecting context changes in a stream ...
Nikita A. Sakhanenko, George F. Luger
ICDAR
2009
IEEE
13 years 2 months ago
Handling Out-of-Vocabulary Words and Recognition Errors Based on Word Linguistic Context for Handwritten Sentence Recognition
In this paper we investigate the use of linguistic information given by language models to deal with word recognition errors on handwritten sentences. We focus especially on error...
Solen Quiniou, Mohamed Cheriet, Éric Anquet...
EMNLP
2007
13 years 6 months ago
A Topic Model for Word Sense Disambiguation
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...
Jordan L. Boyd-Graber, David M. Blei, Xiaojin Zhu