Thai Natural Language Processing: Word Segmentation, Semantic Analysis, and Application

✍ Scribed by Chalermpol Tapsai, Herwig Unger, Phayung Meesad

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 194
• Series: Studies in Computational Intelligence, 918
• Category: Library

✦ Synopsis

This book presents comprehensive solutions for readers wanting to develop their own Natural Language Processing projects for the Thai language. Starting from the fundamental principles of Thai, it discusses each step in Natural Language Processing, and the real-world applications. In addition to theory, it also includes practical workshops for readers new to the field who want to start programming in Natural Language Processing. Moreover, it features a number of new techniques to provide readers with ideas for developing their own projects. The book details Thai words using phonetic annotation and also includes English definitions to help readers understand the content.

✦ Table of Contents

Preface
Contents
1 Introduction
1.1 Natural Language Processing
1.2 Fundamental Knowledge of Thai Language Principles
1.2.1 Thai Alphabets
1.2.2 Thai Word
1.2.3 Transforming of Verbs into Nouns
1.2.4 Transforming of Adjectives into Nouns
1.2.5 Transforming of Adjectives into Adverbs
1.2.6 Numeral and Quantity Representation
1.2.7 Quantifying Noun
1.3 Thai Sentences
References
2 Thai Word Segmentation
2.1 Syllable Segmentation
2.2 Word Segmentation
2.3 Trie Is Not Tree
2.4 Word Segmentation Based on Surrounding Contexts
2.5 Comparison of Thai Segmentation Algorithms
2.6 Problems in Thai Word Segmentation
References
3 TLS-ART-MC, A New Algorithm for Thai Word Segmentation
3.1 The TLS-ART-MC Algorithm
3.2 Datasets
3.3 Model Development and Evaluation
3.4 Ranking Trie
3.4.1 Ranking Trie Creation Algorithm
3.5 Word Usage Frequency Analysis
3.5.1 Text Corpus
3.5.2 The Results of Word Usage Frequency Analysis
3.5.3 Character Statistics
3.5.4 Consonants and Vowels
3.5.5 Word Types
3.6 Word Segmentation with Automatic Ranking Trie
3.7 Solving Problems of Misspelling and Various Spelling Patterns
3.7.1 Soundex
3.7.2 Traditional Soundex Code
3.7.3 Completed Soundex
3.7.4 Completed Soundex Encoding
3.7.5 Completed Soundex Encoding Process
3.7.6 Completed Soundex Similarity Values
3.7.7 Evaluation of Completed Soundex
3.7.8 The Experiment for Performance Evaluation
3.8 Conclusion
References
4 Semantic Analysis
4.1 Pattern Parsing
4.2 Ontology
4.3 Semantic Pattern
4.4 Summarization
References
5 Thai Natural Language Processing Programming
5.1 NLP Programming Tools
5.2 Basic Programming with Python
5.3 Control Statements
5.3.1 If Statements
5.3.2 Nested-If Statements
5.4 Loop Statements
5.4.1 While Statements
5.4.2 For Statements
5.5 Workshop: Development of NLP Program (English)
5.6 Workshop: Development of NLP Program (Thai)
5.7 Summarization
References
6 The Application of Thai Natural Language Processing
6.1 Conceptual Framework
6.2 The Model Development
6.3 Fuzzy Data Processing
6.4 Functional Testing and Model Improvement
6.5 Performance Evaluation of the Model
6.6 Summarization
References
Glossary and Transcription
Appendix