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ICML
2005
IEEE
14 years 6 months ago
Exploiting syntactic, semantic and lexical regularities in language modeling via directed Markov random fields
We present a directed Markov random field (MRF) model that combines n-gram models, probabilistic context free grammars (PCFGs) and probabilistic latent semantic analysis (PLSA) fo...
Shaojun Wang, Shaomin Wang, Russell Greiner, Dale ...
SOFSEM
2000
Springer
13 years 8 months ago
Towards High Speed Grammar Induction on Large Text Corpora
Abstract. In this paper we describe an e cient and scalable implementation for grammar induction based on the EMILE approach ( 2], 3], 4], 5], 6]). The current EMILE 4.1 implementa...
Pieter W. Adriaans, Marten Trautwein, Marco Vervoo...
TCS
2008
13 years 4 months ago
Computation of distances for regular and context-free probabilistic languages
Several mathematical distances between probabilistic languages have been investigated in the literature, motivated by applications in language modeling, computational biology, syn...
Mark-Jan Nederhof, Giorgio Satta
AEI
2006
108views more  AEI 2006»
13 years 5 months ago
Grammatical rules for specifying information for automated product data modeling
This paper presents a linguistic framework for developing a formal knowledge acquisition method. The framework is intended to empower domain experts to specify information require...
Ghang Lee, Charles M. Eastman, Rafael Sacks, Shamk...