A natural language based indexing technique for Chinese information retrieval.

Pang Chun Kiu.Thesis (M.Phil.)--Chinese University of Hong Kong, 1997.Includes bibliographical references (leaves 101-107).Chapter 1 --- Introduction --- p.2Chapter 1.1 --- Chinese Indexing using Noun Phrases --- p.6Chapter 1.2 --- Objectives --- p.8Chapter 1.3 --- An Overview of the Thesis --- p.8Chapter 2 --- Background --- p.10Chapter 2.1 --- Technology Influences on Information Retrieval --- p.10Chapter 2.2 --- Related Work --- p.13Chapter 2.2.1 --- Statistical/Keyword Approaches --- p.13Chapter 2.2.2 --- Syntactical approaches --- p.15Chapter 2.2.3 --- Semantic approaches --- p.17Chapter 2.2.4 --- Noun Phrases Approach --- p.18Chapter 2.2.5 --- Chinese Information Retrieval --- p.20Chapter 2.3 --- Our Approach --- p.21Chapter 3 --- Chinese Noun Phrases --- p.23Chapter 3.1 --- Different types of Chinese Noun Phrases --- p.23Chapter 3.2 --- Ambiguous noun phrases --- p.27Chapter 3.2.1 --- Ambiguous English Noun Phrases --- p.27Chapter 3.2.2 --- Ambiguous Chinese Noun Phrases --- p.28Chapter 3.2.3 --- Statistical data on the three NPs --- p.33Chapter 4 --- Index Extraction from De-de Conj. NP --- p.35Chapter 4.1 --- Word Segmentation --- p.36Chapter 4.2 --- Part-of-speech tagging --- p.37Chapter 4.3 --- Noun Phrase Extraction --- p.37Chapter 4.4 --- The Chinese noun phrase partial parser --- p.38Chapter 4.5 --- Handling Parsing Ambiguity --- p.40Chapter 4.6 --- Index Building Strategy --- p.41Chapter 4.7 --- The cross-set generation rules --- p.44Chapter 4.8 --- Example 1: Indexing De-de NP --- p.46Chapter 4.9 --- Example 2: Indexing Conjunctive NP --- p.48Chapter 4.10 --- Experimental results and Discussion --- p.49Chapter 5 --- Indexing Compound Nouns --- p.52Chapter 5.1 --- Previous Researches on Compound Nouns --- p.53Chapter 5.2 --- Indexing two-term Compound Nouns --- p.55Chapter 5.2.1 --- About the thesaurus《同義詞詞林》 --- p.56Chapter 5.3 --- Indexing Compound Nouns of three or more terms --- p.58Chapter 5.4 --- Corpus learning approach --- p.59Chapter 5.4.1 --- An Example --- p.60Chapter 5.4.2 --- Experimental Setup --- p.63Chapter 5.4.3 --- An Experiment using the third level of the Cilin --- p.65Chapter 5.4.4 --- An Experiment using the second level of the Cilin --- p.66Chapter 5.5 --- Contextual Approach --- p.68Chapter 5.5.1 --- The algorithm --- p.69Chapter 5.5.2 --- An Illustrative Example --- p.71Chapter 5.5.3 --- Experiments on compound nouns --- p.72Chapter 5.5.4 --- Experiment I: Word Distance Based Extraction --- p.73Chapter 5.5.5 --- Experiment II: Semantic Class Based Extraction --- p.75Chapter 5.5.6 --- Experiments III: On different boundaries --- p.76Chapter 5.5.7 --- The Final Algorithm --- p.79Chapter 5.5.8 --- Experiments on other compounds --- p.82Chapter 5.5.9 --- Discussion --- p.83Chapter 6 --- Overall Effectiveness --- p.85Chapter 6.1 --- Illustrative Example for the Integrated Algorithm --- p.86Chapter 6.2 --- Experimental Setup --- p.90Chapter 6.3 --- Experimental Results & Discussion --- p.91Chapter 7 --- Conclusion --- p.95Chapter 7.1 --- Summary --- p.95Chapter 7.2 --- Contributions --- p.97Chapter 7.3 --- Future Directions --- p.98Chapter 7.3.1 --- Word-sense determination --- p.98Chapter 7.3.2 --- Hybrid approach for compound noun indexing --- p.99Chapter A --- Cross-set Generation Rules --- p.108Chapter B --- Tag set by Tsinghua University --- p.110Chapter C --- Noun Phrases Test Set --- p.113Chapter D --- Compound Nouns Test Set --- p.124Chapter D.l --- Three-term Compound Nouns --- p.125Chapter D.1.1 --- NVN --- p.125Chapter D.1.2 --- Other three-term compound nouns --- p.129Chapter D.2 --- Four-term Compound Nouns --- p.133Chapter D.3 --- Five-term and six-term Compound Nouns --- p.13