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

Knowledge has always been a decisive factor of humankind's social evolutions. Collecting the world's knowledge is one of the greatest challenges of our civilization. Knowledge involves the use of information but information is not knowledge. It is a way of acquiring and understanding information. Improving the visibility and the accessibility of information requires to organize it efficiently. This thesis focuses on this general purpose.<p><p>A fundamental objective of computer science is to store and retrieve information efficiently. This is known as the dictionary problem. A dictionary asks for a data structure which allows essentially the search operation. In general, information that is important and popular at a given time has to be accessed faster than less relevant information. This can be achieved by dynamically managing the data structure periodically such that relevant information is located closer from the search starting point. The second part of this thesis is devoted to the development and the understanding of self-adjusting dictionaries in various models of computation. In particular, we focus our attention on dictionaries which do not have any knowledge of the future accesses. Those dictionaries have to auto-adapt themselves to be competitive with dictionaries specifically tuned for a given access sequence. <p><p>This approach, which transforms the information structure, is not always feasible. Reasons can be that the structure is based on the semantic of the information such as categorization. In this context, the search procedure is linked to the structure itself and modifying the structure will affect how a search is performed. A solution developed to improve search in static structure is the hotlink assignment. It is a way to enhance a structure without altering its original design. This approach speeds up the search by creating shortcuts in the structure. The first part of this thesis is devoted to this approach. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished