RNA MODELING BY COMBINING STOCHASTIC CONTEXT-FREE GRAMMARS AND n-GRAM MODELS
| Autor: | Ismael Salvador, José-Miguel Benedí |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
Computer science
Stochastic modelling business.industry Bigram Context-free grammar Syntactic pattern recognition computer.software_genre Grammar induction n-gram Rule-based machine translation Artificial Intelligence Synchronous context-free grammar Computer Vision and Pattern Recognition Artificial intelligence business computer Software Natural language processing |
| Zdroj: | International Journal of Pattern Recognition and Artificial Intelligence. 16:309-315 |
| ISSN: | 1793-6381 0218-0014 |
| DOI: | 10.1142/s0218001402001691 |
| Popis: | The RNA sentences present structured regions caused by pairwise correlations, and nonstructured regions where any global relation can be found. In this paper, we present a combination of stochastic context-free grammars (SCFG) and bigram models. The SCFGs are used to represent the long-term relations of the structured part of RNA sequences, while the bigram models are used to capture the local relations of the nonstructured part. A stochastic version of Sakakibara's algorithm is used to study the SCFGs. Finally, experiments to evaluate the behavior of this proposal were carried out. |
| Databáze: | OpenAIRE |
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