A new approach for extracting inter-word semantic relationship from a contemporary Chinese thesaurus.

by Lam Sze-sing.Thesis (M.Phil.)--Chinese University of Hong Kong, 1995.Includes bibliographical references (leaves 119-123).Chapter CHAPTER 1 --- INTRODUCTION --- p.1Chapter 1.1 --- Introduction --- p.1Chapter 1.2 --- Statement of Thesis --- p.5Chapter 1.3 --- Organization of this Thesis --- p.6Chapter CHAPTER 2 --- RELATED WORK --- p.8Chapter 2.1 --- Overview --- p.8Chapter 2.2 --- Corpus-Based Knowledge Acquisition --- p.12Chapter 2.3 --- Linguistic-Based Knowledge Acquisition --- p.18Chapter 2.3.1 --- Knowledge Acquisition from Standard Dictionaries --- p.18Chapter 2.3.2 --- Knowledge Acquisition from Standard Thesauri --- p.23Chapter 2.4 --- Remarks --- p.24Chapter CHAPTER 3 --- A METHOD TO EXTRACT THE INTER-WORD SEMANTIC RELATIONSHIP FROM《同義詞詞林》 --- p.25Chapter 3.1 --- Background --- p.25Chapter 3.1.1 --- Structure of《《同義詞詞林》 --- p.26Chapter 3.1.2 --- Knowledge Representation of a Machine Tractable Thesaurus --- p.28Chapter 3.1.3 --- Extracting the Semantic Knowledge by Simple Co-occurrence --- p.28Chapter 3.2 --- Association Network --- p.31Chapter 3.3 --- Semantic Association Model --- p.33Chapter 3.3.1 --- Problems with the Simple Co-occurrence Method --- p.34Chapter 3.3.2 --- Methodology of Semantic Association Model --- p.39Chapter 3.4 --- Inter-word Semantic Function ..… --- p.51Chapter CHAPTER 4 --- NOUN-VERB-NOUN COMPOUND WORD DETECTION : AN EXPERIMENT --- p.55Chapter 4.1 --- Overview --- p.56Chapter 4.2 --- N-V-N Compound Word Detection Model --- p.61Chapter 4.3 --- Experimental Results of N-V-N Compound Word Detection --- p.63Chapter CHAPTER 5 --- WORD SENSE DISAMBIGUATION : AN APPLICATION … --- p.66Chapter 5.1 --- Overview --- p.67Chapter 5.2 --- Word-Sense Disambiguation Model --- p.72Chapter 5.2.1 --- Linguistic Resource --- p.72Chapter 5.2.2 --- The LSD-C Algorithm --- p.73Chapter 5.2.3 --- LSD-C in Action --- p.78Chapter 5.3 --- Experimental Results of Word Sense Disambiguation --- p.83Chapter CHAPTER 6 --- CONCLUSIONS & FURTHER RESEARCH --- p.93Chapter 6.1 --- Conclusions --- p.93Chapter 6.2 --- Further Research --- p.96Chapter 6.2.1 --- Enriching the Knowledge --- p.96Chapter 6.2.2 --- Enhancing the N-V-N Compound Word Detection Model --- p.98Chapter 6.2.3 --- Enhancing the LSD-C Algorithm --- p.99APPENDICES --- p.101Appendix A - Dependency Grammar --- p.101Appendix B - Sample Articles from a Local Chinese Newspaper --- p.104Appendix C - Ambiguous Words with the Senses Given by《現代漢語詞 典》 --- p.108Appendix D - List of Stop Words for the Testing Samples --- p.117REFERENCES --- p.11