Читать книгу Automatic Text Simplification - Horacio Saggion - Страница 8
ОглавлениеContents
1.3 The Need for Text Simplification
1.4 Easy-to-read Material on the Web
2 Readability and Text Simplification
2.3 Advanced Natural Language Processing for Readability Assessment
2.3.2 Readability as Classification
2.3.3 Discourse, Semantics, and Cohesion in Assessing Readability
2.5 Are Classic Readability Formulas Correlated?
2.6 Sentence-level Readability Assessment
3.1 A First Approach
3.2 Lexical Simplification in LexSiS
3.3 Assessing Word Difficulty
3.4 Using Comparable Corpora
3.4.1 Using Simple English Wikipedia Edit History
3.4.2 Using Wikipedia and Simple Wikipedia
3.5 Language Modeling for Lexical Simplification
3.6 Lexical Simplification Challenge
3.7 Simplifying Numerical Expressions in Text
3.8 Conclusion
3.9 Further Reading
4.1 First Steps in Syntactic Simplification
4.2 Syntactic Simplification and Cohesion
4.3 Rule-based Syntactic Simplification using Syntactic Dependencies
4.4 Pattern Matching over Dependencies with JAPE
4.5 Simplifying Complex Sentences by Extracting Key Events
4.6 Conclusion
4.7 Further Reading
5.1 Simplification as Translation
5.1.1 Learning Simple English
5.1.2 Facing Strong Simplifications
5.2 Learning Sentence Transformations
5.3 Optimizing Rule Application
5.4 Learning from a Semantic Representation
5.5 Conclusion
5.6 Further Reading
6 Full Text Simplification Systems
6.1 Text Simplification in PSET
6.2 Text Simplification in Simplext
6.2.1 Rule-based “Lexical” Simplification
6.2.2 Computational Grammars for Simplification
6.2.3 Evaluating Simplext
6.3 Text Simplification in PorSimples
6.3.1 An Authoring Tool with Simplification Capabilities
6.4 Conclusion
6.5 Further Reading
7 Applications of Automatic Text Simplification
7.1 Simplification for Specific Target Populations
7.1.1 Automatic Text Simplification for Reading Assistance
7.1.2 Simplification for Dyslexic Readers
7.1.3 Simplification-related Techniques for People with Autism Spectrum Disorder
7.1.4 Natural Language Generation for Poor Readers
7.2 Text Simplification as NLP Facilitator
7.2.1 Simplification for Parsing
7.2.2 Simplification for Information Extraction
7.2.3 Simplification in and for Text Summarization
7.2.4 Simplifying Medical Literature
7.2.5 Retrieving Facts from Simplified Sentences
7.2.6 Simplifying Patent Documents
7.3 Conclusion
7.4 Further Reading
8 Text Simplification Resources and Evaluation
8.1 Lexical Resources for Simplification Applications
8.2 Lexical Simplification Resources
8.3 Corpora
8.4 Non-English Text Simplification Datasets
8.5 Evaluation
8.6 Toward Automatically Measuring the Quality of Simplified Output
8.7 Conclusion
8.8 Further Reading
