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NAACL
2003
15 years 8 months ago
A Generative Probabilistic OCR Model for NLP Applications
In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing f...
Okan Kolak, William J. Byrne, Philip Resnik
EMNLP
2010
15 years 4 months ago
A Latent Variable Model for Geographic Lexical Variation
The rapid growth of geotagged social media raises new computational possibilities for investigating geographic linguistic variation. In this paper, we present a multi-level genera...
Jacob Eisenstein, Brendan O'Connor, Noah A. Smith,...
EMNLP
2009
15 years 4 months ago
Polylingual Topic Models
Topic models are a useful tool for analyzing large text collections, but have previously been applied in only monolingual, or at most bilingual, contexts. Meanwhile, massive colle...
David M. Mimno, Hanna M. Wallach, Jason Naradowsky...
IEEEICCI
2006
IEEE
16 years 18 days ago
SenseNet: A Knowledge Representation Model for Computational Semantics
Knowledge representation is essential for semantics modeling and intelligent information processing. For decades researchers have proposed many knowledge representation techniques...
Ping Chen, Wei Ding 0003, Chengmin Ding
CIKM
2011
Springer
14 years 6 months ago
Towards noise-resilient document modeling
We introduce a generative probabilistic document model based on latent Dirichlet allocation (LDA), to deal with textual errors in the document collection. Our model is inspired by...
Tao Yang, Dongwon Lee