by Raymond Cheuk-kuen Chen. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 157-160). / Chapter 1. --- INTRODUCTION --- p.8 / Chapter 1.1. --- Windowing System --- p.8 / Chapter 1.2. --- Fonts --- p.10 / Chapter 1.2.1. --- Bitmap Fonts --- p.11 / Chapter 1.2.2. --- Outline Fonts --- p.12 / Chapter 1.3. --- Different font support models --- p.15 / Chapter 1.3.1. --- Supported by applications --- p.15 / Chapter 1.3.2. --- Supported by windowing system --- p.17 / Chapter 1.3.'3. --- Supported by a dedicated server --- p.19 / Chapter 1.4. --- Issues of Chinese Font Support --- p.20 / Chapter 2. --- OVERVIEW OF X WINDOW SYSTEM --- p.22 / Chapter 2.1. --- Introduction --- p.22 / Chapter 2.2. --- Architecture --- p.23 / Chapter 2.3. --- Font Management in the X Window System --- p.23 / Chapter 2.3.1. --- Before X Version 11 Release5 --- p.24 / Chapter 2.3.2. --- In X Version 11 Release5 --- p.25 / Chapter 2.3.3. --- Portable Compiled Format --- p.25 / Chapter 2.3.4. --- Font Server --- p.26 / Chapter 2.3.5. --- Font Management Library --- p.28 / Chapter 2.4. --- Internal Code --- p.29 / Chapter 3. --- CHINESE FONT SERVER --- p.30 / Chapter 3.1. --- Motivation --- p.30 / Chapter 3.2. --- Font Server Architecture --- p.31 / Chapter 3.2.1. --- Device Independent Font Server layer(DIFS) --- p.32 / Chapter 3.2.2. --- Operating System layer(OS) --- p.32 / Chapter 3.2.3. --- Font Management Library(FML) --- p.33 / Chapter 3.2.4. --- Font Path Element --- p.34 / Chapter 3.2.5. --- Font File Renderer --- p.35 / Chapter 3.2.6. --- Font server Renderer --- p.36 / Chapter 3.3. --- Implementation of Chinese Font Server --- p.36 / Chapter 3.3.1. --- Font data and code set --- p.36 / Chapter 3.3.2. --- Registering a new font reader --- p.38 / Chapter 3.3.3. --- Font specific functions --- p.42 / Chapter 3.3.4. --- Load-All Scheme --- p.43 / Chapter 3.3.5. --- Demand-Loading Scheme --- p.44 / Chapter 3.3.6. --- Embedding of font rasterizer --- p.44 / Chapter 3.4. --- Test Results --- p.45 / Chapter 3.4.1. --- X Application Tests --- p.45 / Chapter 3.4.2. --- Demand-Loading Test --- p.49 / Chapter 3.5. --- Some Remarks --- p.53 / Chapter 4. --- OVERVIEW OF PRINTING SYSTEM --- p.54 / Chapter 4.1. --- Motivation --- p.54 / Chapter 4.2. --- Design Considerations --- p.56 / Chapter 4.2.1. --- Modification of the X server --- p.56 / Chapter 4.2.2. --- Embed the printing system into the font server --- p.57 / Chapter 4.2.3. --- Distributed Architecture --- p.58 / Chapter 4.3. --- System Architecture --- p.60 / Chapter 4.4. --- Printer Server --- p.61 / Chapter 4.5. --- Font Server --- p.63 / Chapter 4.6. --- Printing Services Protocols --- p.63 / Chapter 4.7. --- X Window System Server --- p.65 / Chapter 4.8. --- Printer Server Library --- p.65 / Chapter 4.9. --- Client Applications --- p.65 / Chapter 5. --- DESIGN AND IMPLEMENTATION OF A PRINTER SERVER --- p.67 / Chapter 5.1. --- Objects identification --- p.67 / Chapter 5.1.1. --- Dispatcher (dispatcher) --- p.68 / Chapter 5.1.2. --- Communication Channel (ComChannel) --- p.68 / Chapter 5.1.3. --- Font Cache Manager (FnCache) --- p.69 / Chapter 5.1.4. --- PrnFont (PrnFont) --- p.69 / Chapter 5.1.5. --- Per-Font Cache (CacheStruct) 一- --- p.70 / Chapter 5.1.6. --- Font Server (FnServer) --- p.71 / Chapter 5.1.7. --- Client Manager (LRUList) --- p.71 / Chapter 5.1.8. --- Client Record (ClientRec) --- p.71 / Chapter 5.1.9. --- Printer Driver (PrnDriver) --- p.71 / Chapter 5.1.10. --- Down Loaded Font Table (DownLoadedFont) --- p.72 / Chapter 5.1.11. --- Request Header (reqHeader) --- p.72 / Chapter 5.1.12. --- Generic Reply(replyGeneric) --- p.74 / Chapter 5.2. --- Objects Organization --- p.74 / Chapter 5.2.1. --- Server Control Subsystem --- p.75 / Chapter 5.2.2. --- Client Management Subsystem --- p.78 / Chapter 5.2.3. --- Request Handling Subsystem --- p.84 / Chapter 5.2.4. --- Font Managing Subsystem --- p.86 / Chapter 6. --- SAMPLE PRINTER DRIVER --- p.94 / Chapter 6.1. --- Printer Control Languages --- p.94 / Chapter 6.1.1. --- Structure of PCL Command --- p.95 / Chapter 6.1.2. --- PCL Command Example --- p.97 / Chapter 6.2. --- Printer Font Resources --- p.98 / Chapter 6.3. --- Traditional Font Handling Methods in a Printer Driver --- p.99 / Chapter 6.4. --- Soft Font Creation in PCL Printer --- p.101 / Chapter 6.4.1. --- Font ID number --- p.102 / Chapter 6.4.2. --- Font Descriptor --- p.102 / Chapter 6.4.3. --- Character Code - --- p.104 / Chapter 6.4.4. --- Character Descriptor --- p.105 / Chapter 6.4.5. --- Character Bitmap Data --- p.107 / Chapter 6.5. --- New font downloading schemes for double-byte fonts --- p.107 / Chapter 6.5.1. --- Terminology --- p.108 / Chapter 6.5.2. --- Underlying Concepts of Algorithm One --- p.109 / Chapter 6.5.3. --- Algorithm One --- p.111 / Chapter 6.5.3.1. --- Code Mapping --- p.112 / Chapter 6.5.3.2. --- Example --- p.114 / Chapter 6.5.3.3. --- Memory Consideration --- p.115 / Chapter 6.5.4. --- Algorithm Two --- p.117 / Chapter 7. --- EXPERIMENT RESULTS AND DISCUSSIONS --- p.121 / Chapter 7.1. --- Cache Test --- p.121 / Chapter 7.2. --- Printer Driver Test --- p.125 / Chapter 7.2.1. --- Testing with 10 points font --- p.126 / Chapter 7.2.2. --- Testing with 12 points font --- p.129 / Chapter 7.2.3. --- Testing with 15 points font --- p.131 / Chapter 7.2.4. --- Testing with 18 points font --- p.134 / Chapter 7.3. --- Time Measurement --- p.136 / Chapter 7.4. --- Discussion --- p.139 / Chapter 7.5. --- Further Improvement --- p.143 / Chapter 8. --- CONCLUSIONS --- p.145 / APPENDIX A. PRINTER DRIVER CLASS --- p.147 / APPENDIX B. SAMPLE OUTPUT --- p.149 / REFERENCES --- p.157

Kwong-ho Wu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 72-75). / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Outline Fonts --- p.2 / Chapter 1.1.1 --- Advantages and Disadvantages --- p.4 / Chapter 1.1.2 --- Representations --- p.4 / Chapter 1.1.3 --- Rasterization --- p.5 / Chapter 1.2 --- Introduction to This Thesis --- p.6 / Chapter 1.2.2 --- Organization --- p.7 / Chapter 1.2.1 --- Objectives --- p.7 / Chapter 2 --- Chinese Characters Fonts --- p.8 / Chapter 2.1 --- Large Character Set --- p.8 / Chapter 2.2 --- Font Styles --- p.8 / Chapter 2.3 --- Storage Problems --- p.9 / Chapter 2.4 --- Hierarchical Structure --- p.10 / Chapter 2.5 --- High Stroke Count --- p.11 / Chapter 3 --- Rasterization --- p.13 / Chapter 3.1 --- The Basic Rasterization --- p.13 / Chapter 3.1.1 --- Scan Conversion --- p.14 / Chapter 3.1.2 --- Filling Outline --- p.16 / Chapter 3.2 --- Font Rasterization --- p.17 / Chapter 3.2.1 --- Outline Scaling --- p.17 / Chapter 3.2.2 --- Hintings --- p.17 / Chapter 3.2.3 --- Basic Rasterization Approach for Chinese Fonts --- p.18 / Chapter 3.3 --- Hintings --- p.20 / Chapter 3.3.1 --- Phase Control --- p.20 / Chapter 3.3.2 --- Auto-Hints --- p.21 / Chapter 3.3.3 --- Storage of Hintings Information in TrueType Font and Postscript Font --- p.22 / Chapter 4 --- An Improved Chinese Font Rasterizer --- p.24 / Chapter 4.1 --- Floating Point Avoidance --- p.24 / Chapter 4.2 --- Filling --- p.25 / Chapter 4.2.1 --- Filling with Horizontal Scan Line --- p.25 / Chapter 4.2.2 --- Filling with Vertical Scan Line --- p.27 / Chapter 4.3 --- Hintings --- p.30 / Chapter 4.3.1 --- Assumptions --- p.30 / Chapter 4.3.2 --- Maintaining Regular Strokes Width --- p.30 / Chapter 4.3.3 --- Maintaining Regular Spacing Among Strokes --- p.34 / Chapter 4.3.4 --- Hintings of Single Stroke Contour --- p.42 / Chapter 4.3.5 --- Storing the Hinting Information in Font File --- p.49 / Chapter 4.4 --- A Rasterization Algorithm for Printing --- p.51 / Chapter 4.4.1 --- A Simple Algorithm for Generating Smooth Characters --- p.52 / Chapter 4.4.2 --- Algorithm --- p.54 / Chapter 4.4.3 --- Results --- p.54 / Chapter 5 --- Experiments --- p.56 / Chapter 5.1 --- Apparatus --- p.56 / Chapter 5.2 --- Experiments for Investigating Rasterization Speed --- p.56 / Chapter 5.2.1 --- Investigation into the Effects of Features of Chinese Fonts on Rasterization Time --- p.56 / Chapter 5.2.2 --- Improvement of Fast Rasterizer --- p.57 / Chapter 5.2.3 --- Details of Experiments --- p.57 / Chapter 5.3 --- Experiments for Rasterization Speed of Font File with Hints --- p.57 / Chapter 6 --- Results and Conclusions --- p.58 / Chapter 6.1 --- Observations --- p.58 / Chapter 6.1.1 --- Relationship Between Time for Rasterization and Stroke Count --- p.58 / Chapter 6.1.2 --- Effects of Style --- p.61 / Chapter 6.1.3 --- Investigation into the Observed Relationship --- p.62 / Chapter 6.2 --- Improvement of the Improved Rasterizer --- p.64 / Chapter 6.3 --- Gain and Cost of Inserting Hints into Font File --- p.68 / Chapter 6.3.1 --- Cost --- p.68 / Chapter 6.3.2 --- Gain --- p.68 / Chapter 6.4 --- Conclusions --- p.69 / Chapter 6.5 --- Future Work --- p.69 / Appendix

Suen Tow Sunny. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 65-67). / Introduction --- p.1 / Chapter 1. --- ACCESS with an Extendible User-friendly X/Chinese Interface --- p.4 / Chapter 1.1. --- System requirement --- p.4 / Chapter 1.1.1. --- User interface issue --- p.4 / Chapter 1.1.2. --- Development issue --- p.5 / Chapter 1.2. --- Development decision --- p.6 / Chapter 1.2.1. --- X window system --- p.6 / Chapter 1.2.2. --- X/Chinese toolkit --- p.7 / Chapter 1.2.3. --- C language --- p.8 / Chapter 1.2.4. --- Source code control system --- p.8 / Chapter 1.3. --- System architecture --- p.9 / Chapter 1.4. --- User interface --- p.10 / Chapter 1.5. --- Sample screen --- p.13 / Chapter 1.6. --- System extension --- p.14 / Chapter 1.7. --- System portability --- p.18 / Chapter 2. --- Study on Algorithms for Automatically Correcting Characters in Chinese Cangjie-typed Text --- p.19 / Chapter 2.1. --- Chinese character input --- p.19 / Chapter 2.1.1. --- Chinese keyboards --- p.20 / Chapter 2.1.2. --- Keyboard redefinition scheme --- p.21 / Chapter 2.2. --- Cangjie input method --- p.24 / Chapter 2.3. --- Review on existing techniques for automatically correcting words in English text --- p.26 / Chapter 2.3.1. --- Nonword error detection --- p.27 / Chapter 2.3.2. --- Isolated-word error correction --- p.28 / Chapter 2.3.2.1. --- Spelling error patterns --- p.29 / Chapter 2.3.2.2. --- Correction techniques --- p.31 / Chapter 2.3.3. --- Context-dependent word correction research --- p.32 / Chapter 2.3.3.1. --- Natural language processing approach --- p.33 / Chapter 2.3.3.2. --- Statistical language model --- p.35 / Chapter 2.4. --- Research on error rates and patterns in Cangjie input method --- p.37 / Chapter 2.5. --- Similarities and differences between Chinese and English typed text --- p.41 / Chapter 2.5.1. --- Similarities --- p.41 / Chapter 2.5.2. --- Differences --- p.42 / Chapter 2.6. --- Proposed algorithm for automatic Chinese text correction --- p.44 / Chapter 2.6.1. --- Sentence level --- p.44 / Chapter 2.6.2. --- Part-of-speech level --- p.45 / Chapter 2.6.3. --- Character level --- p.47 / Conclusion --- p.50 / Appendix A Cangjie Radix Table --- p.51 / Appendix B Sample Text --- p.52 / Article 1 --- p.52 / Article 2 --- p.53 / Article 3 --- p.56 / Article 4 --- p.58 / Appendix C Error Statistics --- p.61 / References --- p.65

by Lam Chin-keung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 129-135 (2nd gp.)). / ACKNOWLEDGMENTS --- p.I / ABSTRACT --- p.II / TABLE OF CONTENTS --- p.III / LIST OF FIGURES --- p.VI / LIST OF TABLES --- p.VIII / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Motivations --- p.1 / Chapter 1.2 --- Objectives --- p.3 / Chapter 1.3 --- More to go --- p.3 / Chapter 1.4 --- Chapter Summary --- p.4 / Chapter CHAPTER 2 --- RELATED WORK --- p.6 / Chapter 2.1 --- Chinese Related Work --- p.6 / Chapter 2.1.1 --- Chinese Natural Language --- p.6 / Chapter 2.1.2 --- Chinesized Query Language From English --- p.7 / Chapter 2.2 --- High Level Database Query Language --- p.8 / Chapter 2.2.1 --- Relational Algebra vs Relational Calculus --- p.9 / Chapter 2.2.2 --- Procedural vs Declarative --- p.10 / Chapter 2.2.3 --- Natural Language (NL) vs Restricted Natural Language (RNL) --- p.11 / Chapter 2.3 --- Database Query Interface --- p.13 / Chapter 2.3.1 --- Linear Textual Interface --- p.13 / Chapter 2.3.2 --- Form-based Interface --- p.14 / Chapter 2.3.3 --- Graphical Interface --- p.14 / Chapter 2.4 --- Remarks --- p.14 / Chapter CHAPTER 3 --- DESIGN PRINCIPLES --- p.16 / Chapter 3.1 --- Underlying Data Model of the new language --- p.16 / Chapter 3.2 --- Problems Under Attack --- p.17 / Chapter 3.2.1 --- Naturalness --- p.17 / Chapter 3.2.2 --- Procedural vs Declarative --- p.19 / Chapter 3.2.3 --- Supports of Chinese Characters --- p.21 / Chapter 3.3 --- Design Principles --- p.22 / Chapter 3.4 --- Chapter Summary --- p.26 / Chapter CHAPTER 4 --- LANGUAGE DEFINITION --- p.28 / Chapter 4.1 --- Language Overvew --- p.28 / Chapter 4.2 --- The Data Manipulation Language --- p.29 / Chapter 4.2.1 --- Relational Operators --- p.30 / Chapter 4.2.2 --- Rail-Track Diagram of Chiql --- p.32 / Chapter 4.2.3 --- The 11-template --- p.33 / Chapter 4.2.4 --- Chiql Examples --- p.37 / Chapter 4.2.5 --- Common Language Constructs --- p.39 / Chapter 4.2.6 --- ONE issue about GROUP BY and RESTRICTION --- p.41 / Chapter 4.3 --- Other Language Features --- p.42 / Chapter 4.3.1 --- Aggregate Functions --- p.43 / Chapter 4.3.2 --- Attribute Alias --- p.44 / Chapter 4.3.3 --- Conditions in Chinese --- p.45 / Chapter 4.3.4 --- Unquantifed Predicates --- p.45 / Chapter 4.3.5 --- sorting --- p.47 / Chapter 4.4 --- Treatment of Quantified Predicates --- p.48 / Chapter 4.5 --- The Data Definition Language --- p.52 / Chapter 4.5.1 --- Create Table --- p.52 / Chapter 4.5.2 --- Drop Table --- p.54 / Chapter 4.5.3 --- Alter Table --- p.54 / Chapter 4.5.4 --- Insert Row --- p.56 / Chapter 4.5.5 --- Delete Row --- p.56 / Chapter 4.5.6 --- Update Row --- p.57 / Chapter 4.5.7 --- Remarks on DDL --- p.58 / Chapter 4.6 --- Chapter Summary --- p.59 / Chapter CHAPTER 5 --- END-USER INTERFACE --- p.61 / Chapter 5.1 --- EUI Overview --- p.61 / Chapter 5.2 --- Design Principles --- p.62 / Chapter 5.2.1 --- Language Independent Aspects --- p.62 / Chapter 5.2.2 --- Language Dependent Aspects --- p.64 / Chapter 5.3 --- Complex Condition Handling --- p.68 / Chapter 5.4 --- Input Sequences of the EUI --- p.71 / Chapter 5.5 --- Query Formulation： An Example --- p.73 / Chapter 5.6 --- Chapter Summary --- p.85 / Chapter CHAPTER 6 --- CHIQL TO SQL TRANSLATIONS --- p.86 / Chapter 6.1 --- Related Work --- p.87 / Chapter 6.2 --- Translation Overview --- p.87 / Chapter 6.2.1 --- "Pass One:Mapping( Input = Chiql, Output = multi-statement SQL)" --- p.89 / Chapter 6.2.2 --- "Pass Two:Nesting(Input = multi-statement SQL, Output = single statement SQL)" --- p.92 / Chapter 6.2.3 --- Technical Difficulties in Chiql/SQL Translation --- p.99 / Chapter 6.3 --- Chapter Summary --- p.106 / Chapter CHAPTER 7 --- EVALUATION --- p.108 / Chapter 7.1 --- Expressiveness Test --- p.108 / Chapter 7.1.1 --- Results --- p.109 / Chapter 7.1.2 --- Implications --- p.111 / Chapter 7.2 --- Usability Evaluation --- p.111 / Chapter 7.2.1 --- Evaluation Methodology --- p.112 / Chapter 7.2.2 --- Result:Completion Time --- p.113 / Chapter 7.2.3 --- Result: Additional Help --- p.116 / Chapter 7.2.4 --- Result： Query Error --- p.116 / Chapter 7.2.5 --- Result： Overall Score --- p.118 / Chapter 7.2.6 --- User Comments --- p.120 / Chapter 7.3 --- Chapter Summary --- p.120 / Chapter CHAPTER 8 --- CONCLUSIONS --- p.122 / Chapter 8.1 --- Thesis Conclusions --- p.122 / Chapter 8.2 --- Future Work --- p.124 / REFERENCES / APPENDIX

by Lam Sze-sing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 119-123). / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 1.2 --- Statement of Thesis --- p.5 / Chapter 1.3 --- Organization of this Thesis --- p.6 / Chapter CHAPTER 2 --- RELATED WORK --- p.8 / Chapter 2.1 --- Overview --- p.8 / Chapter 2.2 --- Corpus-Based Knowledge Acquisition --- p.12 / Chapter 2.3 --- Linguistic-Based Knowledge Acquisition --- p.18 / Chapter 2.3.1 --- Knowledge Acquisition from Standard Dictionaries --- p.18 / Chapter 2.3.2 --- Knowledge Acquisition from Standard Thesauri --- p.23 / Chapter 2.4 --- Remarks --- p.24 / Chapter CHAPTER 3 --- A METHOD TO EXTRACT THE INTER-WORD SEMANTIC RELATIONSHIP FROM《同義詞詞林》 --- p.25 / Chapter 3.1 --- Background --- p.25 / Chapter 3.1.1 --- Structure of《《同義詞詞林》 --- p.26 / Chapter 3.1.2 --- Knowledge Representation of a Machine Tractable Thesaurus --- p.28 / Chapter 3.1.3 --- Extracting the Semantic Knowledge by Simple Co-occurrence --- p.28 / Chapter 3.2 --- Association Network --- p.31 / Chapter 3.3 --- Semantic Association Model --- p.33 / Chapter 3.3.1 --- Problems with the Simple Co-occurrence Method --- p.34 / Chapter 3.3.2 --- Methodology of Semantic Association Model --- p.39 / Chapter 3.4 --- Inter-word Semantic Function ..… --- p.51 / Chapter CHAPTER 4 --- NOUN-VERB-NOUN COMPOUND WORD DETECTION : AN EXPERIMENT --- p.55 / Chapter 4.1 --- Overview --- p.56 / Chapter 4.2 --- N-V-N Compound Word Detection Model --- p.61 / Chapter 4.3 --- Experimental Results of N-V-N Compound Word Detection --- p.63 / Chapter CHAPTER 5 --- WORD SENSE DISAMBIGUATION : AN APPLICATION … --- p.66 / Chapter 5.1 --- Overview --- p.67 / Chapter 5.2 --- Word-Sense Disambiguation Model --- p.72 / Chapter 5.2.1 --- Linguistic Resource --- p.72 / Chapter 5.2.2 --- The LSD-C Algorithm --- p.73 / Chapter 5.2.3 --- LSD-C in Action --- p.78 / Chapter 5.3 --- Experimental Results of Word Sense Disambiguation --- p.83 / Chapter CHAPTER 6 --- CONCLUSIONS & FURTHER RESEARCH --- p.93 / Chapter 6.1 --- Conclusions --- p.93 / Chapter 6.2 --- Further Research --- p.96 / Chapter 6.2.1 --- Enriching the Knowledge --- p.96 / Chapter 6.2.2 --- Enhancing the N-V-N Compound Word Detection Model --- p.98 / Chapter 6.2.3 --- Enhancing the LSD-C Algorithm --- p.99 / APPENDICES --- p.101 / Appendix A - Dependency Grammar --- p.101 / Appendix B - Sample Articles from a Local Chinese Newspaper --- p.104 / Appendix C - Ambiguous Words with the Senses Given by《現代漢語詞 典》 --- p.108 / Appendix D - List of Stop Words for the Testing Samples --- p.117 / REFERENCES --- p.119

Ng Mau Kit Michael. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 117-120). / Abstract and appendix in English and Chinese. / Abstract --- p.i / Acknowledgments --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background Knowledge and Basic Concepts --- p.7 / Chapter 2.1 --- Classification of Natural Languages --- p.7 / Chapter 2.2 --- Chinese Spell Checking --- p.9 / Chapter 2.3 --- Characteristics of Chinese --- p.12 / Chapter 2.3.1 --- Word Frequency and Statistical Information of Chinese Words --- p.12 / Chapter 2.3.2 --- Chinese Grammar --- p.15 / Chapter 2.3.2.1 --- Word Class --- p.15 / Chapter 2.3.2.2 --- Grammar Rules --- p.17 / Chapter 3 --- Problems with Chinese Spell Checking and Related Work --- p.18 / Chapter 3.1 --- Ambiguities --- p.19 / Chapter 3.2 --- Unknown Words --- p.20 / Chapter 3.3 --- Text Errors --- p.21 / Chapter 3.4 --- Combinatory Explosion --- p.23 / Chapter 3.5 --- Related Work --- p.26 / Chapter 4 --- The Chinese Spell Checking System --- p.33 / Chapter 4.1 --- Architecutre of the Chinese Spell Checking System (CSCS) --- p.35 / Chapter 4.2 --- The Segmenter and the Error Detector --- p.39 / Chapter 5 --- The Block-of-Combinations Segmentation Algorithm and Error Detection --- p.42 / Chapter 5.1 --- Single-character-word Function --- p.43 / Chapter 5.2 --- Segmentation Strategy --- p.46 / Chapter 5.3 --- Maximum Number of Combinations of the BOC --- p.51 / Chapter 5.4 --- A Case Study of the BOC --- p.54 / Chapter 5.5 --- Evaluation of the BOC --- p.59 / Chapter 5.5.1 --- Accuracy --- p.59 / Chapter 5.5.2 --- Speed --- p.61 / Chapter 5.5.3 --- Discussion --- p.62 / Chapter 5.6 --- Experiments on Error Detection for the BOC --- p.63 / Chapter 5.6.1 --- Experimental Results of the Error Detection for the BOC --- p.65 / Chapter 6 --- The Genetic Algorithm Segmentation Method --- p.69 / Chapter 6.1 --- Basic Concepts of Genetic Algorithm --- p.69 / Chapter 6.2 --- Genetic Algorithm Model --- p.73 / Chapter 6.2.1 --- Chromosome Representation --- p.75 / Chapter 6.2.2 --- The Flow of the GAS --- p.76 / Chapter 6.2.2.1 --- Crossover --- p.77 / Chapter 6.2.2.2 --- Replacement --- p.78 / Chapter 6.2.2.3 --- Mutation --- p.80 / Chapter 6.2.2.4 --- Termination Criteria --- p.80 / Chapter 6.2.3 --- Fitness Function --- p.81 / Chapter 6.2.3.1 --- Single-character-word Function --- p.82 / Chapter 6.2.3.2 --- Known-word Function and Unknown-word Function --- p.83 / Chapter 6.2.3.3 --- Grammar Rules Scoring Function --- p.83 / Chapter 6.3 --- Maximum Number of Combinations of the GAS --- p.86 / Chapter 6.4 --- Evaluation of the GAS --- p.86 / Chapter 6.5 --- Discussion --- p.88 / Chapter 7 --- The Improved-BOC Algorithm for Handling Unknown Words and Errors --- p.90 / Chapter 7.1 --- Segmentation Principle of the Improved-BOC Method --- p.91 / Chapter 7.2 --- Improvement of the Scoring Function --- p.93 / Chapter 7.2.1 --- The Choice of Grammar Rules --- p.93 / Chapter 7.2.2 --- Phrase-structure Style --- p.96 / Chapter 7.2.3 --- Computer Model of Grammar Rules for Handling Unknown Words --- p.98 / Chapter 7.3 --- Evaluation of Segmentation --- p.102 / Chapter 7.4 --- Error Detection --- p.104 / Chapter 7.4.1 --- Evaluation of Error Detection --- p.106 / Chapter 7.5 --- Discussion --- p.108 / Chapter 7.6 --- "Comparison between the MM, BOC, GA and Improved-BOC" --- p.109 / Chapter 8 --- Conclusion --- p.114 / Bibliography --- p.117 / Appendix A: Sample Result of the Genetic Algorithm Segmentation Method --- p.121 / Appendix B: Set of Grammar Rules --- p.123

Hu Ke. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 56-58). / Abstracts in English and Chinese.

Siu, Kai-Chung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 99-106). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Thesis Outline --- p.5 / Chapter 2 --- Background --- p.6 / Chapter 2.1 --- Natural Language Understanding --- p.6 / Chapter 2.1.1 --- Rule-based Approaches --- p.7 / Chapter 2.1.2 --- Stochastic Approaches --- p.8 / Chapter 2.1.3 --- Phrase-Spotting Approaches --- p.9 / Chapter 2.2 --- Grammar Induction --- p.10 / Chapter 2.2.1 --- Semantic Classification Trees --- p.11 / Chapter 2.2.2 --- Simulated Annealing --- p.12 / Chapter 2.2.3 --- Bayesian Grammar Induction --- p.12 / Chapter 2.2.4 --- Statistical Grammar Induction --- p.13 / Chapter 2.3 --- Machine Translation --- p.14 / Chapter 2.3.1 --- Rule-based Approach --- p.15 / Chapter 2.3.2 --- Statistical Approach --- p.15 / Chapter 2.3.3 --- Example-based Approach --- p.16 / Chapter 2.3.4 --- Knowledge-based Approach --- p.16 / Chapter 2.3.5 --- Evaluation Method --- p.19 / Chapter 3 --- Semi-Automatic Grammar Induction --- p.20 / Chapter 3.1 --- Agglomerative Clustering --- p.20 / Chapter 3.1.1 --- Spatial Clustering --- p.21 / Chapter 3.1.2 --- Temporal Clustering --- p.24 / Chapter 3.1.3 --- Free Parameters --- p.26 / Chapter 3.2 --- Post-processing --- p.27 / Chapter 3.3 --- Chapter Summary --- p.29 / Chapter 4 --- Application to the ATIS Domain --- p.30 / Chapter 4.1 --- The ATIS Domain --- p.30 / Chapter 4.2 --- Parameters Selection --- p.32 / Chapter 4.3 --- Unsupervised Grammar Induction --- p.35 / Chapter 4.4 --- Prior Knowledge Injection --- p.40 / Chapter 4.5 --- Evaluation --- p.43 / Chapter 4.5.1 --- Parse Coverage in Understanding --- p.45 / Chapter 4.5.2 --- Parse Errors --- p.46 / Chapter 4.5.3 --- Analysis --- p.47 / Chapter 4.6 --- Chapter Summary --- p.49 / Chapter 5 --- Portability to Chinese --- p.50 / Chapter 5.1 --- Corpus Preparation --- p.50 / Chapter 5.1.1 --- Tokenization --- p.51 / Chapter 5.2 --- Experiments --- p.52 / Chapter 5.2.1 --- Unsupervised Grammar Induction --- p.52 / Chapter 5.2.2 --- Prior Knowledge Injection --- p.56 / Chapter 5.3 --- Evaluation --- p.58 / Chapter 5.3.1 --- Parse Coverage in Understanding --- p.59 / Chapter 5.3.2 --- Parse Errors --- p.60 / Chapter 5.4 --- Grammar Comparison Across Languages --- p.60 / Chapter 5.5 --- Chapter Summary --- p.64 / Chapter 6 --- Bi-directional Machine Translation --- p.65 / Chapter 6.1 --- Bilingual Dictionary --- p.67 / Chapter 6.2 --- Concept Alignments --- p.68 / Chapter 6.3 --- Translation Procedures --- p.73 / Chapter 6.3.1 --- The Matching Process --- p.74 / Chapter 6.3.2 --- The Searching Process --- p.76 / Chapter 6.3.3 --- Heuristics to Aid Translation --- p.81 / Chapter 6.4 --- Evaluation --- p.82 / Chapter 6.4.1 --- Coverage --- p.83 / Chapter 6.4.2 --- Performance --- p.86 / Chapter 6.5 --- Chapter Summary --- p.89 / Chapter 7 --- Conclusions --- p.90 / Chapter 7.1 --- Summary --- p.90 / Chapter 7.2 --- Future Work --- p.92 / Chapter 7.2.1 --- Suggested Improvements on Grammar Induction Process --- p.92 / Chapter 7.2.2 --- Suggested Improvements on Bi-directional Machine Trans- lation --- p.96 / Chapter 7.2.3 --- Domain Portability --- p.97 / Chapter 7.3 --- Contributions --- p.97 / Bibliography --- p.99 / Chapter A --- Original SQL Queries --- p.107 / Chapter B --- Induced Grammar --- p.109 / Chapter C --- Seeded Categories --- p.111

Ip Chun Wah Timmy. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 113-120). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Topic Detection and Tracking --- p.2 / Chapter 1.1.1 --- What is a Topic? --- p.3 / Chapter 1.1.2 --- What is Topic Tracking? --- p.4 / Chapter 1.2 --- Research Contributions --- p.4 / Chapter 1.2.1 --- Named Entity Tagging --- p.5 / Chapter 1.2.2 --- Handling Unknown Words --- p.6 / Chapter 1.2.3 --- Named-Entity Approach in Topic Tracking --- p.7 / Chapter 1.3 --- Organization of Thesis --- p.7 / Chapter 2 --- Background --- p.9 / Chapter 2.1 --- Previous Developments in Topic Tracking --- p.10 / Chapter 2.1.1 --- BBN's Tracking System --- p.10 / Chapter 2.1.2 --- CMU's Tracking System --- p.11 / Chapter 2.1.3 --- Dragon's Tracking System --- p.12 / Chapter 2.1.4 --- UPenn's Tracking System --- p.13 / Chapter 2.2 --- Topic Tracking in Chinese --- p.13 / Chapter 2.3 --- Part-of-Speech Tagging --- p.15 / Chapter 2.3.1 --- A Brief Overview of POS Tagging --- p.15 / Chapter 2.3.2 --- Transformation-based Error-Driven Learning --- p.18 / Chapter 2.4 --- Unknown Word Identification --- p.20 / Chapter 2.4.1 --- Rule-based approaches --- p.21 / Chapter 2.4.2 --- Statistical approaches --- p.23 / Chapter 2.4.3 --- Hybrid approaches --- p.24 / Chapter 2.5 --- Information Retrieval Models --- p.25 / Chapter 2.5.1 --- Vector-Space Model --- p.26 / Chapter 2.5.2 --- Probabilistic Model --- p.27 / Chapter 2.6 --- Chapter Summary --- p.28 / Chapter 3 --- System Overview --- p.29 / Chapter 3.1 --- Segmenter --- p.30 / Chapter 3.2 --- TEL Tagger --- p.31 / Chapter 3.3 --- Unknown Words Identifier --- p.32 / Chapter 3.4 --- Topic Tracker --- p.33 / Chapter 3.5 --- Chapter Summary --- p.34 / Chapter 4 --- Named Entity Tagging --- p.36 / Chapter 4.1 --- Experimental Data --- p.37 / Chapter 4.2 --- Transformational Tagging --- p.41 / Chapter 4.2.1 --- Notations --- p.41 / Chapter 4.2.2 --- Corpus Utilization --- p.42 / Chapter 4.2.3 --- Lexical Rules --- p.42 / Chapter 4.2.4 --- Contextual Rules --- p.47 / Chapter 4.3 --- Experiment and Result --- p.49 / Chapter 4.3.1 --- Lexical Tag Initialization --- p.50 / Chapter 4.3.2 --- Contribution of Lexical and Contextual Rules --- p.52 / Chapter 4.3.3 --- Performance on Unknown Words --- p.56 / Chapter 4.3.4 --- A Possible Benchmark --- p.57 / Chapter 4.3.5 --- Comparison between TEL Approach and the Stochas- tic Approach --- p.58 / Chapter 4.4 --- Chapter Summary --- p.59 / Chapter 5 --- Handling Unknown Words in Topic Tracking --- p.62 / Chapter 5.1 --- Overview --- p.63 / Chapter 5.2 --- Person Names --- p.64 / Chapter 5.2.1 --- Forming possible named entities from OOV by group- ing n-grams --- p.66 / Chapter 5.2.2 --- Overlapping --- p.69 / Chapter 5.3 --- Organization Names --- p.71 / Chapter 5.4 --- Location Names --- p.73 / Chapter 5.5 --- Dates and Times --- p.74 / Chapter 5.6 --- Chapter Summary --- p.75 / Chapter 6 --- Topic Tracking in Chinese --- p.77 / Chapter 6.1 --- Introduction of Topic Tracking --- p.78 / Chapter 6.2 --- Experimental Data --- p.79 / Chapter 6.3 --- Evaluation Methodology --- p.81 / Chapter 6.3.1 --- Cost Function --- p.82 / Chapter 6.3.2 --- DET Curve --- p.83 / Chapter 6.4 --- The Named Entity Approach --- p.85 / Chapter 6.4.1 --- Designing the Named Entities Set for Topic Tracking --- p.85 / Chapter 6.4.2 --- Feature Selection --- p.86 / Chapter 6.4.3 --- Integrated with Vector-Space Model --- p.87 / Chapter 6.5 --- Experimental Results and Analysis --- p.91 / Chapter 6.5.1 --- Notations --- p.92 / Chapter 6.5.2 --- Stopword Elimination --- p.92 / Chapter 6.5.3 --- TEL Tagging --- p.95 / Chapter 6.5.4 --- Unknown Word Identifier --- p.100 / Chapter 6.5.5 --- Error Analysis --- p.106 / Chapter 6.6 --- Chapter Summary --- p.108 / Chapter 7 --- Conclusions and Future Work --- p.110 / Chapter 7.1 --- Conclusions --- p.110 / Chapter 7.2 --- Future Work --- p.111 / Bibliography --- p.113 / Chapter A --- The POS Tags --- p.121 / Chapter B --- Surnames and transliterated characters --- p.123 / Chapter C --- Stopword List for Person Name --- p.126 / Chapter D --- Organization suffixes --- p.127 / Chapter E --- Location suffixes --- p.128 / Chapter F --- Examples of Feature Table (Train set with condition D410) --- p.129

Wong Kam Lai. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 92-98). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Our Contributions --- p.5 / Chapter 1.2 --- Organization of this Thesis --- p.5 / Chapter 2 --- Literature Review --- p.7 / Chapter 2.1 --- Dragon Systems --- p.7 / Chapter 2.2 --- Carnegie Mellon University (CMU) --- p.9 / Chapter 2.3 --- University of Massachusetts (UMass) --- p.10 / Chapter 2.4 --- IBM T.J. Watson Research Center --- p.11 / Chapter 2.5 --- BBN Technologies --- p.12 / Chapter 2.6 --- National Taiwan University (NTU) --- p.13 / Chapter 2.7 --- Drawbacks of Existing Approaches --- p.14 / Chapter 3 --- Overview of Proposed Approach --- p.15 / Chapter 3.1 --- News Source --- p.15 / Chapter 3.2 --- Story Preprocessing --- p.18 / Chapter 3.3 --- Concept Term Generation --- p.20 / Chapter 3.4 --- Named Entity Extraction --- p.21 / Chapter 3.5 --- Gross Translation of Chinese to English --- p.21 / Chapter 3.6 --- Topic Detection method --- p.22 / Chapter 3.6.1 --- Deferral Period --- p.22 / Chapter 3.6.2 --- Detection Approach --- p.23 / Chapter 4 --- Concept Term Model --- p.25 / Chapter 4.1 --- Background of Contextual Analysis --- p.25 / Chapter 4.2 --- Concept Term Generation --- p.28 / Chapter 4.2.1 --- Concept Generation Algorithm --- p.28 / Chapter 4.2.2 --- Concept Term Representation for Detection --- p.33 / Chapter 5 --- Topic Detection Model --- p.35 / Chapter 5.1 --- Text Representation and Term Weights --- p.35 / Chapter 5.1.1 --- Story Representation --- p.35 / Chapter 5.1.2 --- Topic Representation --- p.43 / Chapter 5.1.3 --- Similarity Score --- p.43 / Chapter 5.1.4 --- Time adjustment scheme --- p.46 / Chapter 5.2 --- Gross Translation Method --- p.48 / Chapter 5.3 --- The Detection System --- p.50 / Chapter 5.3.1 --- Detection Requirement --- p.50 / Chapter 5.3.2 --- The Top Level Model --- p.52 / Chapter 5.4 --- The Clustering Algorithm --- p.55 / Chapter 5.4.1 --- Similarity Calculation --- p.55 / Chapter 5.4.2 --- Grouping Related Elements --- p.56 / Chapter 5.4.3 --- Topic Identification --- p.60 / Chapter 6 --- Experimental Results and Analysis --- p.63 / Chapter 6.1 --- Evaluation Model --- p.63 / Chapter 6.1.1 --- Evaluation Methodology --- p.64 / Chapter 6.2 --- Experiments on the effects of tuning the parameter --- p.68 / Chapter 6.2.1 --- Experiment Setup --- p.68 / Chapter 6.2.2 --- Results and Analysis --- p.69 / Chapter 6.3 --- Experiments on the effects of named entities and concept terms --- p.74 / Chapter 6.3.1 --- Experiment Setup --- p.74 / Chapter 6.3.2 --- Results and Analysis --- p.75 / Chapter 6.4 --- Experiments on the effect of using time adjustment --- p.77 / Chapter 6.4.1 --- Experiment Setup --- p.77 / Chapter 6.4.2 --- Results and Analysis --- p.79 / Chapter 6.5 --- Experiments on mono-lingual detection --- p.80 / Chapter 6.5.1 --- Experiment Setup --- p.80 / Chapter 6.5.2 --- Results and Analysis --- p.80 / Chapter 7 --- Conclusions and Future Work --- p.83 / Chapter 7.1 --- Conclusions --- p.83 / Chapter 7.2 --- Future Work --- p.85 / Chapter A --- List of Topics annotated for TDT3 Corpus --- p.86 / Chapter B --- Matching evaluation topics to hypothesized topics --- p.90 / Bibliography --- p.92