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» A Generative Probabilistic OCR Model for NLP Applications
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NAACL
2003
13 years 5 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
ICPR
2000
IEEE
13 years 8 months ago
Stochastic Error-Correcting Parsing for OCR Post-Processing
In this paper, stochastic error-correcting parsing is proposed as a powerful and flexible method to post-process the results of an optical character recognizer (OCR). Determinist...
Juan Carlos Pérez-Cortes, Juan-Carlos Ameng...
GRAMMARS
2002
119views more  GRAMMARS 2002»
13 years 4 months ago
Computational Complexity of Probabilistic Disambiguation
Recent models of natural language processing employ statistical reasoning for dealing with the ambiguity of formal grammars. In this approach, statistics, concerning the various li...
Khalil Sima'an
ACSC
2006
IEEE
13 years 10 months ago
Shallow NLP techniques for internet search
Information Retrieval (IR) is a major component in many of our daily activities, with perhaps its most prominent role manifested in search engines. Today’s most advanced engines...
Alex Penev, Raymond K. Wong
EACL
2010
ACL Anthology
13 years 6 months ago
Probabilistic Approaches for Modeling Text Structure and Their Application to Text-to-Text Generation
Abstract. Since the early days of generation research, it has been acknowledged that modeling the global structure of a document is crucial for producing coherent, readable output....
Regina Barzilay