Rethinking language models within the framework of dynamic bayesian networks
Identifieur interne :
000564 ( PascalFrancis/Corpus );
précédent :
000563;
suivant :
000565
Rethinking language models within the framework of dynamic bayesian networks
Auteurs : Murat Deviren ;
Khalid Daoudi ;
Kamel SmaïliSource :
-
Lecture notes in computer science [ 0302-9743 ] ; 2005.
RBID : Pascal:05-0286437
Descripteurs français
English descriptors
Abstract
We present a new approach for language modeling based on dynamic Bayesian networks. The philosophy behind this architecture is to learn from data the appropriate relations of dependency between the linguistic variables used in language modeling process. It is an original and coherent framework that processes words and classes in the same model. This approach leads to new data-driven language models capable of outperforming classical ones, sometimes with lower computational complexity. We present experiments on a small and medium corpora. The results show that this new technique is very promising and deserves further investigations.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
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| A08 | 01 | 1 | ENG | @1 Rethinking language models within the framework of dynamic bayesian networks |
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| A09 | 01 | 1 | ENG | @1 Advances in artificial intelligence : Victoria BC, 9-11 May 2005 |
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| A11 | 01 | 1 | | @1 DEVIREN (Murat) |
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| A11 | 02 | 1 | | @1 DAOUDI (Khalid) |
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| A11 | 03 | 1 | | @1 SMAÏLI (Kamel) |
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| A12 | 01 | 1 | | @1 KEGL (Balazs) @9 ed. |
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| A12 | 02 | 1 | | @1 LAPALME (Guy) @9 ed. |
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| C01 | 01 | | ENG | @0 We present a new approach for language modeling based on dynamic Bayesian networks. The philosophy behind this architecture is to learn from data the appropriate relations of dependency between the linguistic variables used in language modeling process. It is an original and coherent framework that processes words and classes in the same model. This approach leads to new data-driven language models capable of outperforming classical ones, sometimes with lower computational complexity. We present experiments on a small and medium corpora. The results show that this new technique is very promising and deserves further investigations. |
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Format Inist (serveur)
| NO : | PASCAL 05-0286437 INIST |
|---|
| ET : | Rethinking language models within the framework of dynamic bayesian networks |
|---|
| AU : | DEVIREN (Murat); DAOUDI (Khalid); SMAÏLI (Kamel); KEGL (Balazs); LAPALME (Guy) |
|---|
| AF : | INRIA-LORIA, Parole team/54602 Villers les Nancy/France (1 aut., 2 aut., 3 aut.) |
|---|
| DT : | Publication en série; Congrès; Niveau analytique |
|---|
| SO : | Lecture notes in computer science; ISSN 0302-9743; Allemagne; Da. 2005; Vol. 3501; Pp. 432-437; Bibl. 8 ref. |
|---|
| LA : | Anglais |
|---|
| EA : | We present a new approach for language modeling based on dynamic Bayesian networks. The philosophy behind this architecture is to learn from data the appropriate relations of dependency between the linguistic variables used in language modeling process. It is an original and coherent framework that processes words and classes in the same model. This approach leads to new data-driven language models capable of outperforming classical ones, sometimes with lower computational complexity. We present experiments on a small and medium corpora. The results show that this new technique is very promising and deserves further investigations. |
|---|
| CC : | 001D02C02 |
|---|
| FD : | Intelligence artificielle; Linguistique; Complexité calcul; Philosophie; Modélisation; Réseau Bayes; Modèle dynamique; Modèle donnée; Architecture basée modèle |
|---|
| ED : | Artificial intelligence; Linguistics; Computational complexity; Philosophy; Modeling; Bayes network; Dynamic model; Data models; Model driven architecture |
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| SD : | Inteligencia artificial; Linguística; Complejidad computación; Filosofía; Modelización; Red Bayes; Modelo dinámico; Arquitectura basada modelo |
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| LO : | INIST-16343.354000124481230470 |
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| ID : | 05-0286437 |
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Links to Exploration step
Pascal:05-0286437
Le document en format XML
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<ET>Rethinking language models within the framework of dynamic bayesian networks</ET>
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