published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

by Hung Doon Chung, Stan. / English and Chinese. / Thesis (M.Ph.)--Chinese University of Hong Kong, 1987. / Bibliography: leaves [163]-[165]

Lee Fu Wing. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 96-104). / Abstract --- p.i / Chapter 1. --- Introduction --- p.1 / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- The contribution of this project --- p.3 / Chapter 1.3 --- Scope of Thesis --- p.3 / Chapter 2. --- Background Study --- p.4 / Chapter 2.1 --- Related works of General DBMS User Interface --- p.4 / Chapter 2.1.1 --- Linear System --- p.4 / Chapter 2.1.2 --- Form-Based System --- p.6 / Chapter 2.1.3 --- Other Approaches --- p.8 / Chapter 2.2 --- Related works of Chinese System --- p.9 / Chapter 2.2.1 --- Artificial Natural Language --- p.9 / Chapter 2.2.2 --- """Chinesized"" English Database Query Language" --- p.9 / Chapter 2.2.3 --- Chiq1 --- p.10 / Chapter 3. --- Design Principles --- p.11 / Chapter 3.1 --- Data Model --- p.11 / Chapter 3.2 --- Language Naturalness --- p.11 / Chapter 3.3 --- Novice Users vs Expert Users --- p.12 / Chapter 3.4 --- Practical Requirements --- p.14 / Chapter 3.4.1 --- Relational Algebra Operators --- p.15 / Chapter 3.4.2 --- Divide and Conquer Querying Strategy --- p.16 / Chapter 3.4.3 --- Unit of Operations --- p.17 / Chapter 3.4.4 --- Graphical User Interface (GUI) --- p.18 / Chapter 3.4.5 --- Direct Object Manipulation --- p.19 / Chapter 3.5 --- SQL Expressiveness --- p.19 / Chapter 4. --- Query Specification in Chinese --- p.21 / Chapter 4.1 --- Defining Elementary Operations --- p.21 / Chapter 5. --- Implementation of the System Design --- p.29 / Chapter 5.1 --- Hardware and Software Configuration --- p.29 / Chapter 5.1.1 --- Basic Components --- p.29 / Chapter 5.1.2 --- Procedures for Data Retrieval --- p.30 / Chapter 5.2 --- System Design --- p.32 / Chapter 5.2.1 --- Common Operations --- p.32 / Chapter 5.2.2 --- Select the Required Tables --- p.33 / Chapter 5.2.3 --- Performing Join --- p.35 / Chapter 5.2.4 --- Performing Restriction --- p.36 / Chapter 5.2.5 --- Performing Projection --- p.37 / Chapter 5.2.6 --- Completion of Query --- p.38 / Chapter 5.2.7 --- Other Basic Operations --- p.39 / Chapter 5.2.8 --- Set Operations --- p.40 / Chapter 5.2.9 --- Composing and Decomposing a Complex Query --- p.41 / Chapter 6. --- Query Formulation in the Interface --- p.42 / Chapter 6.1 --- Example 1 (Simple Query - Novice User) --- p.45 / Chapter 6.2 --- Example 2 (Simple Query - Expert User) --- p.65 / Chapter 6.3 --- Example 3 (Simple Query with Group-By Feature) --- p.77 / Chapter 6.4 --- Example 4 (Complex Query with Set Operations) --- p.87 / Chapter 7. --- Summary and Conclusions --- p.90 / Chapter 7.1 --- Summary of Accomplishment --- p.90 / Chapter 7.2 --- Future Work --- p.94 / Chapter 7.3 --- Conclusion --- p.95 / Chapter 8. --- References --- p.96 / Chapter 9. --- Appendix A : 66 Testing Queries --- p.105 / Chapter 10. --- Appendix B : Glossary --- p.112 / Chapter 11. --- Appendix C : Programs Listing --- p.115

published_or_final_version / abstract / toc / Computer Science and Information Systems / Master / Master of Philosophy

by Jacqueline, Wai-ting Wong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (p. 107-109). / Abstract --- p.i / Acknowledgement --- p.iii / List of Tables --- p.viii / List of Figures --- p.ix / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Chinese Information Processing --- p.6 / Chapter 2.1 --- Chinese Word Segmentation --- p.7 / Chapter 2.1.1 --- Statistical Method --- p.8 / Chapter 2.1.2 --- Probabilistic Method --- p.9 / Chapter 2.1.3 --- Linguistic Method --- p.10 / Chapter 2.2 --- Automatic Indexing --- p.10 / Chapter 2.2.1 --- Title Indexing --- p.11 / Chapter 2.2.2 --- Free-Text Searching --- p.11 / Chapter 2.2.3 --- Citation Indexing --- p.12 / Chapter 2.3 --- Information Retrieval Systems --- p.13 / Chapter 2.3.1 --- Users' Assessment of IRS --- p.13 / Chapter 2.4 --- Concluding Remarks --- p.15 / Chapter 3 --- Survey on Classification --- p.16 / Chapter 3.1 --- Text Classification --- p.17 / Chapter 3.2 --- Survey on Classification Schemes --- p.18 / Chapter 3.2.1 --- Commonly Used Classification Systems --- p.18 / Chapter 3.2.2 --- Classification of Newspapers --- p.31 / Chapter 3.3 --- Concluding Remarks --- p.37 / Chapter 4 --- System Models and the ACTION Algorithm --- p.38 / Chapter 4.1 --- Factors Affecting Systems Performance --- p.38 / Chapter 4.1.1 --- Specificity --- p.39 / Chapter 4.1.2 --- Exhaustivity --- p.40 / Chapter 4.2 --- Assumptions and Scope --- p.42 / Chapter 4.2.1 --- Assumptions --- p.42 / Chapter 4.2.2 --- System Scope ´ؤ Data Flow Diagrams --- p.44 / Chapter 4.3 --- System Models --- p.48 / Chapter 4.3.1 --- Article --- p.48 / Chapter 4.3.2 --- Matching Table --- p.49 / Chapter 4.3.3 --- Forest --- p.51 / Chapter 4.3.4 --- Matching --- p.53 / Chapter 4.4 --- Classification Rules --- p.54 / Chapter 4.5 --- The ACTION Algorithm --- p.56 / Chapter 4.5.1 --- Algorithm Design Objectives --- p.56 / Chapter 4.5.2 --- Measuring Node Significance --- p.56 / Chapter 4.5.3 --- Pseudocodes --- p.61 / Chapter 4.6 --- Concluding Remarks --- p.64 / Chapter 5 --- Analysis of Results and Validation --- p.66 / Chapter 5.1 --- Seeking for Exhaustivity Rather Than Specificity --- p.67 / Chapter 5.1.1 --- The News Article --- p.67 / Chapter 5.1.2 --- The Matching Results --- p.68 / Chapter 5.1.3 --- The Keyword Values --- p.68 / Chapter 5.1.4 --- Analysis of Classification Results --- p.71 / Chapter 5.2 --- Catering for Hierarchical Relationships Between Classes and Subclasses --- p.72 / Chapter 5.2.1 --- The News Article --- p.72 / Chapter 5.2.2 --- The Matching Results --- p.73 / Chapter 5.2.3 --- The Keyword Values --- p.74 / Chapter 5.2.4 --- Analysis of Classification Results --- p.75 / Chapter 5.3 --- A Representative With Zero Occurrence --- p.78 / Chapter 5.3.1 --- The News Article --- p.78 / Chapter 5.3.2 --- The Matching Results --- p.79 / Chapter 5.3.3 --- The Keyword Values --- p.80 / Chapter 5.3.4 --- Analysis of Classification Results --- p.81 / Chapter 5.4 --- Statistical Analysis --- p.83 / Chapter 5.4.1 --- Classification Results with Highest Occurrence Frequency --- p.83 / Chapter 5.4.2 --- Classification Results with Zero Occurrence Frequency --- p.85 / Chapter 5.4.3 --- Distribution of Classification Results on Level Numbers --- p.86 / Chapter 5.5 --- Concluding Remarks --- p.87 / Chapter 5.5.1 --- Advantageous Characteristics of ACTION --- p.88 / Chapter 6 --- Conclusion --- p.93 / Chapter 6.1 --- Perspectives in Document Representation --- p.93 / Chapter 6.2 --- Classification Schemes --- p.95 / Chapter 6.3 --- Classification System Model --- p.95 / Chapter 6.4 --- The ACTION Algorithm --- p.96 / Chapter 6.5 --- Advantageous Characteristics of the ACTION Algorithm --- p.96 / Chapter 6.6 --- Testing and Validating the ACTION algorithm --- p.98 / Chapter 6.7 --- Future Work --- p.99 / Chapter 6.8 --- A Final Remark --- p.100 / Chapter A --- System Models --- p.102 / Chapter B --- Classification Rules --- p.104 / Chapter C --- Node Significance Definitions --- p.105 / References --- p.107

Huang Ruizhang. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 110-114). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Defitition of Topic and Event --- p.2 / Chapter 1.2 --- Event and Topic Discovery --- p.2 / Chapter 1.2.1 --- Problem Definition --- p.2 / Chapter 1.2.2 --- Characteristics of the Discovery Problems --- p.3 / Chapter 1.2.3 --- Our Contributions --- p.5 / Chapter 1.3 --- Story Link Detection --- p.5 / Chapter 1.3.1 --- Problem Definition --- p.5 / Chapter 1.3.2 --- Our Contributions --- p.6 / Chapter 1.4 --- Thesis Organization --- p.7 / Chapter 2 --- Literature Review --- p.8 / Chapter 2.1 --- University of Massachusetts (UMass) --- p.8 / Chapter 2.1.1 --- Topic Detection Approach --- p.8 / Chapter 2.1.2 --- Story Link Detection Approach --- p.9 / Chapter 2.2 --- BBN Technologies --- p.10 / Chapter 2.3 --- IBM Research Center --- p.11 / Chapter 2.4 --- Carnegie Mellon University (CMU) --- p.12 / Chapter 2.4.1 --- Topic Detection Approach --- p.12 / Chapter 2.4.2 --- Story Link Detection Approach --- p.14 / Chapter 2.5 --- National Taiwan University (NTU) --- p.14 / Chapter 2.5.1 --- Topic Detection Approach --- p.14 / Chapter 2.5.2 --- Story Link Detection Approach --- p.15 / Chapter 3 --- System Overview --- p.17 / Chapter 3.1 --- News Sources --- p.18 / Chapter 3.2 --- Story Preprocessing --- p.24 / Chapter 3.3 --- Information Extraction --- p.25 / Chapter 3.4 --- Gloss Translation --- p.26 / Chapter 3.5 --- Term Weight Calculation --- p.30 / Chapter 3.6 --- Event And Topic Discovery --- p.31 / Chapter 3.7 --- Story Link Detection --- p.33 / Chapter 4 --- Event And Topic Discovery --- p.34 / Chapter 4.1 --- Overview of Event and Topic discovery --- p.34 / Chapter 4.2 --- Event Discovery Component --- p.37 / Chapter 4.2.1 --- Overview of Event Discovery Algorithm --- p.37 / Chapter 4.2.2 --- Similarity Calculation --- p.39 / Chapter 4.2.3 --- Story and Event Combination --- p.43 / Chapter 4.2.4 --- Event Discovery Output --- p.44 / Chapter 4.3 --- Topic Discovery Component --- p.45 / Chapter 4.3.1 --- Overview of Topic Discovery Algorithm --- p.47 / Chapter 4.3.2 --- Relevance Model --- p.47 / Chapter 4.3.3 --- Event and Topic Combination --- p.50 / Chapter 4.3.4 --- Topic Discovery Output --- p.50 / Chapter 5 --- Event And Topic Discovery Experimental Results --- p.54 / Chapter 5.1 --- Testing Corpus --- p.54 / Chapter 5.2 --- Evaluation Methodology --- p.56 / Chapter 5.3 --- Experimental Results on Event Discovery --- p.58 / Chapter 5.3.1 --- Parameter Tuning --- p.58 / Chapter 5.3.2 --- Event Discovery Result --- p.59 / Chapter 5.4 --- Experimental Results on Topic Discovery --- p.62 / Chapter 5.4.1 --- Parameter Tuning --- p.64 / Chapter 5.4.2 --- Topic Discovery Results --- p.64 / Chapter 6 --- Story Link Detection --- p.67 / Chapter 6.1 --- Topic Types --- p.67 / Chapter 6.2 --- Overview of Link Detection Component --- p.68 / Chapter 6.3 --- Automatic Topic Type Categorization --- p.70 / Chapter 6.3.1 --- Training Data Preparation --- p.70 / Chapter 6.3.2 --- Feature Selection --- p.72 / Chapter 6.3.3 --- Training and Tuning Categorization Model --- p.73 / Chapter 6.4 --- Link Detection Algorithm --- p.74 / Chapter 6.4.1 --- Story Component Weight --- p.74 / Chapter 6.4.2 --- Story Link Similarity Calculation --- p.76 / Chapter 6.5 --- Story Link Detection Output --- p.77 / Chapter 7 --- Link Detection Experimental Results --- p.80 / Chapter 7.1 --- Testing Corpus --- p.80 / Chapter 7.2 --- Topic Type Categorization Result --- p.81 / Chapter 7.3 --- Link Detection Evaluation Methodology --- p.82 / Chapter 7.4 --- Experimental Results on Link Detection --- p.83 / Chapter 7.4.1 --- Language Normalization Factor Tuning --- p.83 / Chapter 7.4.2 --- Link Detection Performance --- p.90 / Chapter 7.4.3 --- Link Detection Performance Breakdown --- p.91 / Chapter 8 --- Conclusions and Future Work --- p.95 / Chapter 8.1 --- Conclusions --- p.95 / Chapter 8.2 --- Future Work --- p.96 / Chapter A --- List of Topic Title Annotated for TDT3 corpus by LDC --- p.98 / Chapter B --- List of Manually Annotated Events for TDT3 Corpus --- p.104 / Bibliography --- p.114