Semi-automatic grammar induction for bidirectional machine translation.

Wong, Chin Chung.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2002.
Includes bibliographical references (leaves 137-143).
s in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Objectives --- p.3
Chapter 1.2 --- Thesis Outline --- p.5
Chapter 2 --- Background in Natural Language Understanding --- p.6
Chapter 2.1 --- Rule-based Approaches --- p.7
Chapter 2.2 --- Corpus-based Approaches --- p.8
Chapter 2.2.1 --- Stochastic Approaches --- p.8
Chapter 2.2.2 --- Phrase-spotting Approaches --- p.9
Chapter 2.3 --- The ATIS Domain --- p.10
Chapter 2.3.1 --- Chinese Corpus Preparation --- p.11
Chapter 3 --- Semi-automatic Grammar Induction - Baseline Approach --- p.13
Chapter 3.1 --- Background in Grammar Induction --- p.13
Chapter 3.1.1 --- Simulated Annealing --- p.14
Chapter 3.1.2 --- Bayesian Grammar Induction --- p.14
Chapter 3.1.3 --- Probabilistic Grammar Acquisition --- p.15
Chapter 3.2 --- Semi-automatic Grammar Induction 一 Baseline Approach --- p.16
Chapter 3.2.1 --- Spatial Clustering --- p.16
Chapter 3.2.2 --- Temporal Clustering --- p.18
Chapter 3.2.3 --- Post-processing --- p.19
Chapter 3.2.4 --- Four Aspects for Enhancements --- p.20
Chapter 3.3 --- Chapter Summary --- p.22
Chapter 4 --- Semi-automatic Grammar Induction - Enhanced Approach --- p.23
Chapter 4.1 --- Evaluating Induced Grammars --- p.24
Chapter 4.2 --- Stopping Criterion --- p.26
Chapter 4.2.1 --- Cross-checking with Recall Values --- p.29
Chapter 4.3 --- Improvements on Temporal Clustering --- p.32
Chapter 4.3.1 --- Evaluation --- p.39
Chapter 4.4 --- Improvements on Spatial Clustering --- p.46
Chapter 4.4.1 --- Distance Measures --- p.48
Chapter 4.4.2 --- Evaluation --- p.57
Chapter 4.5 --- Enhancements based on Intelligent Selection --- p.62
Chapter 4.5.1 --- Informed Selection between Spatial Clustering and Tem- poral Clustering --- p.62
Chapter 4.5.2 --- Selecting the Number of Clusters Per Iteration --- p.64
Chapter 4.5.3 --- An Example for Intelligent Selection --- p.64
Chapter 4.5.4 --- Evaluation --- p.68
Chapter 4.6 --- Chapter Summary --- p.71
Chapter 5 --- Bidirectional Machine Translation using Induced Grammars ´ؤBaseline Approach --- p.73
Chapter 5.1 --- Background in Machine Translation --- p.75
Chapter 5.1.1 --- Rule-based Machine Translation --- p.75
Chapter 5.1.2 --- Statistical Machine Translation --- p.76
Chapter 5.1.3 --- Knowledge-based Machine Translation --- p.77
Chapter 5.1.4 --- Example-based Machine Translation --- p.78
Chapter 5.1.5 --- Evaluation --- p.79
Chapter 5.2 --- Baseline Configuration on Bidirectional Machine Translation System --- p.84
Chapter 5.2.1 --- Bilingual Dictionary --- p.84
Chapter 5.2.2 --- Concept Alignments --- p.85
Chapter 5.2.3 --- Translation Process --- p.89
Chapter 5.2.4 --- Two Aspects for Enhancements --- p.90
Chapter 5.3 --- Chapter Summary --- p.91
Chapter 6 --- Bidirectional Machine Translation ´ؤ Enhanced Approach --- p.92
Chapter 6.1 --- Concept Alignments --- p.93
Chapter 6.1.1 --- Enhanced Alignment Scheme --- p.95
Chapter 6.1.2 --- Experiment --- p.97
Chapter 6.2 --- Grammar Checker --- p.100
Chapter 6.2.1 --- Components for Grammar Checking --- p.101
Chapter 6.3 --- Evaluation --- p.117
Chapter 6.3.1 --- Bleu Score Performance --- p.118
Chapter 6.3.2 --- Modified Bleu Score --- p.122
Chapter 6.4 --- Chapter Summary --- p.130
Chapter 7 --- Conclusions --- p.131
Chapter 7.1 --- Summary --- p.131
Chapter 7.2 --- Contributions --- p.134
Chapter 7.3 --- Future work --- p.136
Bibliography --- p.137
Chapter A --- Original SQL Queries --- p.144
Chapter B --- Seeded Categories --- p.146
Chapter C --- 3 Alignment Categories --- p.147
Chapter D --- Labels of Syntactic Structures in Grammar Checker --- p.148
http://library.cuhk.edu.hk/record=b5895983
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