Empirical Methods in Natural Language Generation Data-oriented Methods and Empirical Evaluation /

Natural language generation (NLG) is a subfield of natural language processing (NLP) that is often characterized as the study of automatically converting non-linguistic representations (e.g., from databases or other knowledge sources) into coherent natural language text. In recent years the field ha...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Krahmer, Emiel (Editor ), Theune, Mariet (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Lecture Notes in Artificial Intelligence, 5790
Temas:
Natural language processing (Computer science).
Artificial intelligence.
Information storage and retrieval systems.
Application software.
Database management.
Data mining.
Natural Language Processing (NLP).
Artificial Intelligence.
Information Storage and Retrieval.
Computer and Information Systems Applications.
Database Management.
Data Mining and Knowledge Discovery.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Text-to-Text Generation
  • Probabilistic Approaches for Modeling Text Structure and Their Application to Text-to-Text Generation
  • Spanning Tree Approaches for Statistical Sentence Generation
  • On the Limits of Sentence Compression by Deletion
  • NLG in Interaction
  • Learning Adaptive Referring Expression Generation Policies for Spoken Dialogue Systems
  • Modelling and Evaluation of Lexical and Syntactic Alignment with a Priming-Based Microplanner
  • Natural Language Generation as Planning under Uncertainty for Spoken Dialogue Systems
  • Referring Expression Generation
  • Generating Approximate Geographic Descriptions
  • A Flexible Approach to Class-Based Ordering of Prenominal Modifiers
  • Attribute-Centric Referring Expression Generation
  • Evaluation of NLG
  • Assessing the Trade-Off between System Building Cost and Output Quality in Data-to-Text Generation
  • Human Evaluation of a German Surface Realisation Ranker
  • Structural Features for Predicting the Linguistic Quality of Text
  • Towards Empirical Evaluation of Affective Tactical NLG
  • Shared Task Challenges for NLG
  • Introducing Shared Tasks to NLG: The TUNA Shared Task Evaluation Challenges
  • Generating Referring Expressions in Context: The GREC Task Evaluation Challenges
  • The First Challenge on Generating Instructions in Virtual Environments.

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