PL360, a Programming Language for the 360 Computers
Journal of the ACM (JACM)
Practical syntactic error recovery
Communications of the ACM
An efficient context-free parsing algorithm
Communications of the ACM
An error-correcting parse algorithm
Communications of the ACM
The Theory of Parsing, Translation, and Compiling
The Theory of Parsing, Translation, and Compiling
What the Compiler Should Tell the User
Compiler Construction, An Advanced Course, 2nd ed.
Error detection and recovery for syntax directed compiler systems
Error detection and recovery for syntax directed compiler systems
Syntactic Recognition of Imperfectly Specified Patterns
IEEE Transactions on Computers
Stochastic Syntactic Decoding for Pattern Classification
IEEE Transactions on Computers
A Stochastic Syntax Analysis Procedure and Its Application to Pattern Classification
IEEE Transactions on Computers
Language Correction Using Probabilistic Grammars
IEEE Transactions on Computers
Adaptive Graphical Pattern Recognition Beyond Connectionist-Based Approaches
Proceedings of the Joint IAPR International Workshops on Advances in Pattern Recognition
Music Structure Analysis and Its Application to Theme Phrase Extraction
ECDL '99 Proceedings of the Third European Conference on Research and Advanced Technology for Digital Libraries
Recent Developments in Pattern Recognition
IEEE Transactions on Computers
Spelling correction using probabilistic methods
Pattern Recognition Letters
| Hi-index | 14.98 |
In this paper, a probabilistic model for error-correcting parsing with substitution, insertion, and deletion errors is introduced. The formulation of maximum-likelihood error-correcting parser (MLECP) by incorporating the noise model into stochastic grammars is also presented. The use of stochastic error-correcting parsers for recognition of noisy and/or distorted patterns results in a process of high accuracy, but with low efficiency. In order to make the syntax analysis more practically feasible, it is proposed to use a sequential classification method for noisy strings processing. Computation results based on the classification experiments of noisy patterns for both nonsequential and sequential error-correcting parsers are presented.