Thesis (Ph. D.)--University of Wisconsin--Madison, 1971. / Typescript. Vita. Includes bibliographical references.

by Tang Siu-Lam. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 48-54). / Appendix in Chinese. / Acknowledgements --- p.I / Abstract --- p.II / Table of Contents --- p.III / Appendix --- p.IV / Introduction --- p.1 / Parsing Models --- p.3 / Possible Causes for the Discrepancies Observed in Past Studies --- p.7 / Language Specific Properties and Parsing --- p.13 / The Present Study --- p.15 / Experiment1 --- p.19 / Method --- p.22 / Results and Discussion --- p.25 / Experiment2 --- p.28 / Method --- p.30 / Results and Discussion --- p.30 / Experiment3 --- p.35 / Method --- p.38 / Results and Discussion --- p.38 / General Discussion --- p.45 / References --- p.43 / Appendix --- p.55 / "Instructions used in Experiments 1, 2, and3" --- p.55

by Angel Suet Yi Tse. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 126-130). / Abstract / Acknowledgements / Table of Contents / List of Tables / List of Figures / Plagiarism Declaration / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Overview --- p.1 / Chapter 1.2 --- Motivation --- p.2 / Chapter 1.3 --- Applications of NP parsing --- p.4 / Chapter 1.4 --- The Hybrid Approach of NP Partial Parsing with Rule Set Derived from de NPs --- p.5 / Chapter 1.5 --- Organization of the Thesis --- p.7 / Chapter Chapter 2 --- Related Work --- p.9 / Chapter 2.1 --- Overview --- p.9 / Chapter 2.2 --- Chinese Versus English Languages --- p.10 / Chapter 2.3 --- Traditional Versus Contemporary Parsing Approaches --- p.15 / Chapter 2.3.1 --- Linguistics-based and Corpus-based Knowledge Acquisition --- p.15 / Chapter 2.3.2 --- Basic Processing Unit --- p.16 / Chapter 2.3.3 --- Related Literature --- p.17 / Chapter 2.4 --- Sentence / Free Text Parsing --- p.18 / Chapter 2.4.1 --- Linguistics-based --- p.18 / Chapter 2.4.2 --- Corpus-based --- p.21 / Chapter 2.5 --- NP Processing --- p.22 / Chapter 2.5.1 --- NP Detection --- p.22 / Chapter 2.5.2 --- NP Partial Parsing --- p.26 / Chapter 2.6 --- Summary --- p.27 / Chapter Chapter 3 --- Knowledge Elicitation for General NP Partial Parsing from De NPs --- p.28 / Chapter 3.1 --- Overview --- p.28 / Chapter 3.2 --- Background --- p.29 / Chapter 3.3 --- Research in De Phrases --- p.33 / Chapter 3.3.1 --- Research of de Phrases in Pure Linguistics --- p.33 / Chapter 3.3.2 --- Research in de Phrases in Computational Linguistics --- p.36 / Chapter 3.4 --- Significance of De Phrases --- p.37 / Chapter 3.4.1 --- Implication to General NP Parsing --- p.37 / Chapter 3.4.2 --- Embedded Knowledge for General NP Parsing --- p.37 / Chapter 3.5 --- Summary --- p.39 / Chapter Chapter 4 --- Knowledge Acquisition Approaches for General NP Partial Parsing --- p.40 / Chapter 4.1 --- Overview --- p.40 / Chapter 4.2 --- Linguistic-based Approach --- p.41 / Chapter 4.3 --- Corpus-based Approach --- p.43 / Chapter 4.3.1 --- Generalization of NP Grammatical Patterns --- p.44 / Chapter 4.3.2 --- Pitfall of Generalization --- p.47 / Chapter 4.4 --- The Hybrid Approach --- p.47 / Chapter 4.4.1 --- Combining Strategies --- p.50 / Chapter 4.4.2 --- Merging Techniques --- p.53 / Chapter 4.5 --- CNP3- The Chinese NP Partial Parser --- p.55 / Chapter 4.5.1 --- The NP Detection and Extraction Unit (DEU) --- p.56 / Chapter 4.5.2 --- The Knowledge Acquisition Unit (KAU) --- p.56 / Chapter 4.5.3 --- The Parsing Unit (PU) --- p.57 / Chapter 4.5.4 --- Internal Representation of Chinese NPs and Grammar Rules --- p.57 / Chapter 4.6 --- Summary --- p.58 / Chapter Chapter 5 --- "Experiments on Linguistics-, Corpus-based and the Hybrid Approaches" --- p.60 / Chapter 5.1 --- Overview --- p.60 / Chapter 5.2 --- Objective of Experiments --- p.61 / Chapter 5.3 --- Experimental Setup --- p.62 / Chapter 5.3.1 --- The Corpora --- p.62 / Chapter 5.3.2 --- The Standard and Extended Tag Sets --- p.64 / Chapter 5.4 --- Overview of Experiments --- p.67 / Chapter 5.5 --- Evaluation of Linguistic De NP Rules (Experiment 1 A) --- p.70 / Chapter 5.5.1 --- Method --- p.71 / Chapter 5.5.2 --- Results --- p.72 / Chapter 5.5.3 --- Analysis --- p.72 / Chapter 5.6 --- Evaluation of Corpus-based Approach (Experiment IB) --- p.74 / Chapter 5.6.1 --- Method --- p.74 / Chapter 5.6.2 --- Results --- p.75 / Chapter 5.6.3 --- Analysis --- p.76 / Chapter 5.6.4 --- Generalization of NP Grammatical Patterns (Experiment 1B'） --- p.76 / Chapter 5.6.5 --- Results after Merging of Rule Sets (Experiment 1C) --- p.77 / Chapter 5.6.6 --- Error Analysis --- p.79 / Chapter 5.7 --- Phase II Evaluation: Test on General NP Parsing (Experiment 2) --- p.82 / Chapter 5.7.1 --- Method --- p.83 / Chapter 5.7.2 --- Results --- p.85 / Chapter 5.7.3 --- Error Analysis --- p.86 / Chapter 5.8 --- Summary --- p.92 / Chapter Chapter 6 --- Reliability Evaluation of the Hybrid Approach --- p.94 / Chapter 6.1 --- Overview --- p.94 / Chapter 6.2 --- Objective --- p.95 / Chapter 6.3 --- The Training and Test Corpora --- p.96 / Chapter 6.4 --- The Knowledge Base --- p.98 / Chapter 6.5 --- Convergence Sequence Tests --- p.99 / Chapter 6.5.1 --- Results of Close Convergence Tests --- p.100 / Chapter 6.5.2 --- Results of Open Convergence Tests --- p.104 / Chapter 6.5.3 --- Conclusions with Convergence Tests --- p.106 / Chapter 6.6 --- Cross Evaluation Tests --- p.106 / Chapter 6.6.1 --- Results --- p.109 / Chapter 6.6.2 --- Conclusions with Cross Evaluation Tests --- p.112 / Chapter 6.7 --- Summary --- p.113 / Chapter Chapter 7 --- Discussion and Conclusions --- p.115 / Chapter 7.1 --- Overview --- p.115 / Chapter 7.2 --- Difficulties Encountered --- p.116 / Chapter 7.2.1 --- Lack of Standard in Part-of-speech Categorization in Chinese Language --- p.116 / Chapter 7.2.2 --- Under or Over-specification of Tag Class in Tag Set --- p.118 / Chapter 7.2.3 --- Difficulty in Nominal Compound NP Analysis --- p.119 / Chapter 7.3 --- Conclusions --- p.120 / Chapter 7.4 --- Future Work --- p.122 / Chapter 7.4.1 --- Full Automation of NP Pattern Generalization --- p.122 / Chapter 7.4.2 --- Incorporation of Semantic Constraints --- p.123 / Chapter 7.4.3 --- Computational Structural Analysis of Nominal Compound NP --- p.124 / References --- p.126 / Appendix A The Extended Tag Set --- p.131 / Appendix B Linguistic Grammar Rules --- p.135 / Appendix C Generalized Grammar Rules --- p.138

Thesis (Ph. D.)--University of California, San Diego, 2002. / Vita. Includes bibliographical references (leaves 136-144).

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references. Available also from UMI Company.

Not available / text

Thesis (B.A.)--Haverford College, Dept. of Computer Science, 2005. / Includes bibliographical references.

Leung Wai Kwong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. / Includes bibliographical references (leaves 90-95). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Motivation --- p.1 / Chapter 1.2 --- Objective --- p.3 / Chapter 1.3 --- Organization of thesis --- p.3 / Chapter 2 --- Background --- p.5 / Chapter 2.1 --- Chinese Noun Phrases Parsing --- p.5 / Chapter 2.2 --- Chinese Noun Phrases --- p.6 / Chapter 2.3 --- Problems with Syntactic Parsing --- p.11 / Chapter 2.3.1 --- Conjunctive Noun Phrases --- p.11 / Chapter 2.3.2 --- De-de Noun Phrases --- p.12 / Chapter 2.3.3 --- Compound Noun Phrases --- p.13 / Chapter 2.4 --- Observations --- p.15 / Chapter 2.4.1 --- Inadequacy in Part-of-Speech Categorization for Chi- nese NLP --- p.16 / Chapter 2.4.2 --- The Need of Semantic in Noun Phrase Parsing --- p.17 / Chapter 2.5 --- Summary --- p.17 / Chapter 3 --- Hybrid Tag-set --- p.19 / Chapter 3.1 --- Objectives --- p.19 / Chapter 3.1.1 --- Resolving Parsing Ambiguities --- p.19 / Chapter 3.1.2 --- Investigation of Nominal Compound Noun Phrases --- p.20 / Chapter 3.2 --- Definition of Hybrid Tag-set --- p.20 / Chapter 3.3 --- Introduction to Cilin --- p.21 / Chapter 3.4 --- Problems with Cilin --- p.23 / Chapter 3.4.1 --- Unknown words --- p.23 / Chapter 3.4.2 --- Multiple Semantic Classes --- p.25 / Chapter 3.5 --- Introduction to Chinese Word Formation --- p.26 / Chapter 3.5.1 --- Disyllabic Word Formation --- p.26 / Chapter 3.5.2 --- Polysyllabic Word Formation --- p.28 / Chapter 3.5.3 --- Observation --- p.29 / Chapter 3.6 --- Automatic Assignment of Hybrid Tag to Chinese Word --- p.31 / Chapter 3.7 --- Summary --- p.34 / Chapter 4 --- Automatic Semantic Assignment --- p.35 / Chapter 4.1 --- Previous Researches on Semantic Tagging --- p.36 / Chapter 4.2 --- SAUW - Automatic Semantic Assignment of Unknown Words --- p.37 / Chapter 4.2.1 --- POS-to-SC Association (Process 1) --- p.38 / Chapter 4.2.2 --- Morphology-based Deduction (Process 2) --- p.39 / Chapter 4.2.3 --- Di-syllabic Word Analysis (Process 3 and 4) --- p.41 / Chapter 4.2.4 --- Poly-syllabic Word Analysis (Process 5) --- p.47 / Chapter 4.3 --- Illustrative Examples --- p.47 / Chapter 4.4 --- Evaluation and Analysis --- p.49 / Chapter 4.4.1 --- Experiments --- p.49 / Chapter 4.4.2 --- Error Analysis --- p.51 / Chapter 4.5 --- Summary --- p.52 / Chapter 5 --- Word Sense Disambiguation --- p.53 / Chapter 5.1 --- Introduction to Word Sense Disambiguation --- p.54 / Chapter 5.2 --- Previous Works on Word Sense Disambiguation --- p.55 / Chapter 5.2.1 --- Linguistic-based Approaches --- p.56 / Chapter 5.2.2 --- Corpus-based Approaches --- p.58 / Chapter 5.3 --- Our Approach --- p.60 / Chapter 5.3.1 --- Bi-gram Co-occurrence Probabilities --- p.62 / Chapter 5.3.2 --- Tri-gram Co-occurrence Probabilities --- p.63 / Chapter 5.3.3 --- Design consideration --- p.65 / Chapter 5.3.4 --- Error Analysis --- p.67 / Chapter 5.4 --- Summary --- p.68 / Chapter 6 --- Hybrid Tag-set for Chinese Noun Phrase Parsing --- p.69 / Chapter 6.1 --- Resolving Ambiguous Noun Phrases --- p.70 / Chapter 6.1.1 --- Experiment --- p.70 / Chapter 6.1.2 --- Results --- p.72 / Chapter 6.2 --- Summary --- p.78 / Chapter 7 --- Conclusion --- p.80 / Chapter 7.1 --- Summary --- p.80 / Chapter 7.2 --- Difficulties Encountered --- p.83 / Chapter 7.2.1 --- Lack of Training Corpus --- p.83 / Chapter 7.2.2 --- Features of Chinese word formation --- p.84 / Chapter 7.2.3 --- Problems with linguistic sources --- p.85 / Chapter 7.3 --- Contributions --- p.86 / Chapter 7.3.1 --- Enrichment to the Cilin --- p.86 / Chapter 7.3.2 --- Enhancement in syntactic parsing --- p.87 / Chapter 7.4 --- Further Researches --- p.88 / Chapter 7.4.1 --- Investigation into words that undergo semantic changes --- p.88 / Chapter 7.4.2 --- Incorporation of more information into the hybrid tag-set --- p.89 / Chapter A --- POS Tag-set by Tsinghua University (清華大學） --- p.96 / Chapter B --- Morphological Rules --- p.100 / Chapter C --- Syntactic Rules for Di-syllabic Words Formation --- p.104

Luk Po Chui. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 97-100). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Efficiency and Memory --- p.2 / Chapter 1.2 --- Ambiguity --- p.3 / Chapter 1.3 --- Robustness --- p.4 / Chapter 1.4 --- Thesis Organization --- p.5 / Chapter 2 --- Background --- p.7 / Chapter 2.1 --- Introduction --- p.7 / Chapter 2.2 --- Context-Free Grammars --- p.8 / Chapter 2.3 --- The LR Parsing Algorithm --- p.9 / Chapter 2.4 --- The Generalized LR Parsing Algorithm --- p.12 / Chapter 2.4.1 --- Graph-Structured Stack --- p.12 / Chapter 2.4.2 --- Packed Shared Parse Forest --- p.14 / Chapter 2.5 --- Time and Space Complexity --- p.16 / Chapter 2.6 --- Related Work on Parsing --- p.17 / Chapter 2.6.1 --- GLR* --- p.17 / Chapter 2.6.2 --- TINA --- p.18 / Chapter 2.6.3 --- PHOENIX --- p.19 / Chapter 2.7 --- Chapter Summary --- p.21 / Chapter 3 --- Grammar Partitioning --- p.22 / Chapter 3.1 --- Introduction --- p.22 / Chapter 3.2 --- Motivation --- p.22 / Chapter 3.3 --- Previous Work on Grammar Partitioning --- p.24 / Chapter 3.4 --- Our Grammar Partitioning Approach --- p.26 / Chapter 3.4.1 --- Definitions and Concepts --- p.26 / Chapter 3.4.2 --- Guidelines for Grammar Partitioning --- p.29 / Chapter 3.5 --- An Example --- p.30 / Chapter 3.6 --- Chapter Summary --- p.34 / Chapter 4 --- Parser Composition --- p.35 / Chapter 4.1 --- Introduction --- p.35 / Chapter 4.2 --- GLR Lattice Parsing --- p.36 / Chapter 4.2.1 --- Lattice with Multiple Granularity --- p.36 / Chapter 4.2.2 --- Modifications to the GLR Parsing Algorithm --- p.37 / Chapter 4.3 --- Parser Composition Algorithms --- p.45 / Chapter 4.3.1 --- Parser Composition by Cascading --- p.46 / Chapter 4 3.2 --- Parser Composition with Predictive Pruning --- p.48 / Chapter 4.3.3 --- Comparison of Parser Composition by Cascading and Parser Composition with Predictive Pruning --- p.54 / Chapter 4.4 --- Chapter Summary --- p.54 / Chapter 5 --- Experimental Results and Analysis --- p.56 / Chapter 5.1 --- Introduction --- p.56 / Chapter 5.2 --- Experimental Corpus --- p.57 / Chapter 5.3 --- ATIS Grammar Development --- p.60 / Chapter 5.4 --- Grammar Partitioning and Parser Composition on ATIS Domain --- p.62 / Chapter 5.4.1 --- ATIS Grammar Partitioning --- p.62 / Chapter 5.4.2 --- Parser Composition on ATIS --- p.63 / Chapter 5.5 --- Ambiguity Handling --- p.66 / Chapter 5.6 --- Semantic Interpretation --- p.69 / Chapter 5.6.1 --- Best Path Selection --- p.69 / Chapter 5.6.2 --- Semantic Frame Generation --- p.71 / Chapter 5.6.3 --- Post-Processing --- p.72 / Chapter 5.7 --- Experiments --- p.73 / Chapter 5.7.1 --- Grammar Coverage --- p.73 / Chapter 5.7.2 --- Size of Parsing Table --- p.74 / Chapter 5.7.3 --- Computational Costs --- p.76 / Chapter 5.7.4 --- Accuracy Measures in Natural Language Understanding --- p.81 / Chapter 5.7.5 --- Summary of Results --- p.90 / Chapter 5.8 --- Chapter Summary --- p.91 / Chapter 6 --- Conclusions --- p.92 / Chapter 6.1 --- Thesis Summary --- p.92 / Chapter 6.2 --- Thesis Contributions --- p.93 / Chapter 6.3 --- Future Work --- p.94 / Chapter 6.3.1 --- Statistical Approach on Grammar Partitioning --- p.94 / Chapter 6.3.2 --- Probabilistic modeling for Best Parse Selection --- p.95 / Chapter 6.3.3 --- Robust Parsing Strategies --- p.96 / Bibliography --- p.97 / Chapter A --- ATIS-3 Grammar --- p.101 / Chapter A.l --- English ATIS-3 Grammar Rules --- p.101 / Chapter A.2 --- Chinese ATIS-3 Grammar Rules --- p.104

by Ho, Kei Shiu Edward. / "June 1996." / Thesis (Ph.D.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (p. 186-193). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Mode of access: World Wide Web.