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ICML
2005
IEEE
15 years 10 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
15 years 29 days 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
14 years 8 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»
14 years 9 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...