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published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

published_or_final_version / Computer Science / Master / Master of Philosophy

published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

published_or_final_version / Computer Science / Master / Master of Philosophy

No description available.

by Yip Wai Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1990. / Bibliography: leaves 132-135. / ABSTRACT / ACKNOWLEDGEMENTS / PART I / Chapter 1 --- OVERVIEW ON SEMANTIC DATA MODELLING APPROACH … --- p.1 / Chapter 2 --- SCOPE OF RESEARCH --- p.4 / Chapter 3 --- CONCEPTUAL STRUCTURE OF SAM* --- p.7 / Chapter 3.1 --- Concepts and Associations --- p.7 / Chapter 3.1.1 --- Membership Association --- p.8 / Chapter 3.1.2 --- Aggregation Association --- p.8 / Chapter 3.1.3 --- Generalization Association --- p.9 / Chapter 3.1.4 --- Interaction Association --- p.10 / Chapter 3.1.5 --- Composition Association --- p.11 / Chapter 3.1.6 --- Cross-Product Association --- p.12 / Chapter 3.1.7 --- Summary Association --- p.13 / Chapter 3.2 --- An Example --- p.14 / Chapter 3.3 --- Occurrences --- p.15 / PART II / Chapter 4 --- SYSTEM OVERVIEW --- p.17 / Chapter 4.1 --- System Objectives --- p.17 / Chapter 4.1.1 --- Data Level --- p.17 / Chapter 4.1.2 --- Meta-Data Level --- p.18 / Chapter 4.2 --- System Characteristics --- p.19 / Chapter 4.3 --- Design Considerations --- p.20 / Chapter 5 --- IMPLEMENTATION CONSIDERATIONS --- p.23 / Chapter 5.1 --- Introduction --- p.23 / Chapter 5.2 --- Data Definition Language for Schema --- p.24 / Chapter 5.3 --- Construction of Directed Acyclic Graph --- p.27 / Chapter 5.4 --- Query Manipulation Language --- p.28 / Chapter 5.4.1 --- Semantic Manipulation Language --- p.29 / Chapter 5.4.1.1 --- Locate Concepts --- p.30 / Chapter 5.4.1.2 --- Retrieve Information About Concepts --- p.30 / Chapter 5.4.1.3 --- Find a Path Between Two Concepts --- p.31 / Chapter 5.4.2 --- Occurrence Manipulation Language --- p.32 / Chapter 5.5 --- Examples --- p.35 / Chapter 6 --- RESULTS AND DISCUSSIONS --- p.41 / Chapter 6.1 --- Allow Non-Homogeneity of Facts about Entities --- p.41 / Chapter 6.2 --- Field Name is Information --- p.42 / Chapter 6.3 --- Description of Group of Information --- p.43 / Chapter 6.4 --- Explicitly Description of Interaction --- p.43 / Chapter 6.5 --- Information about Entities --- p.44 / Chapter 6.6 --- Automatically Joining Tables --- p.45 / Chapter 6.7 --- Automatically Union Tables --- p.45 / Chapter 6.8 --- Automatically Select Tables --- p.46 / Chapter 6.9 --- Ambiguity --- p.47 / Chapter 6.10 --- Normalization --- p.47 / Chapter 6.11 --- Update --- p.50 / PART III / Chapter 7 --- SCHEMA VERIFICATION --- p.55 / Chapter 7.1 --- Introduction --- p.55 / Chapter 7.2 --- Need of Schema Verification --- p.57 / Chapter 7.3 --- Integrity Constraint Handling Vs Schema Verification --- p.58 / Chapter 8 --- AUTOMATIC THEOREM PROVING --- p.60 / Chapter 8.1 --- Overview --- p.60 / Chapter 8.2 --- A Discussion on Some Automatic Theorem Proving Methods --- p.61 / Chapter 8.2.1 --- Resolution --- p.61 / Chapter 8.2.2 --- Natural Deduction --- p.63 / Chapter 8.2.3 --- Tableau Proof Methods --- p.65 / Chapter 8.2.4 --- Connection Method --- p.67 / Chapter 8.3 --- Comparison of Automatic Theorem Proving Methods --- p.70 / Chapter 8.3.1 --- Proof Procedure --- p.70 / Chapter 8.3.2 --- Overhead --- p.70 / Chapter 8.3.3 --- Unification --- p.71 / Chapter 8.3.4 --- Heuristics --- p.72 / Chapter 8.3.5 --- Getting Lost --- p.73 / Chapter 8.4 --- The Choice of Tool for Schema Verification --- p.73 / Chapter 9 --- IMPROVEMENT OF CONNECTION METHOD --- p.77 / Chapter 9.1 --- Motivation of Improving Connection Method --- p.77 / Chapter 9.2 --- Redundancy Handled by the Original Algorithm --- p.78 / Chapter 9.3 --- Design Philosophy of the Improved Version --- p.82 / Chapter 9.4 --- Primary Connection Method Algorithm --- p.83 / Chapter 9.5 --- AND/OR Connection Graph --- p.89 / Chapter 9.6 --- Graph Traversal Procedure --- p.91 / Chapter 9.7 --- Elimination Redundancy Using AND/OR Connection Graph --- p.94 / Chapter 9.8 --- Further Improvement on Graph Traversal --- p.96 / Chapter 9.9 --- Comparison with Original Connection Method Algorithm --- p.97 / Chapter 9.10 --- Application of Connection Method to Schema Verification --- p.98 / Chapter 9.10.1 --- Express Constraint in Well Formed Formula --- p.98 / Chapter 9.10.2 --- Convert Formula into Negation Normal Form --- p.101 / Chapter 9.10.3 --- Verification --- p.101 / PART IV / Chapter 10 --- FURTHER DEVELOPMENT --- p.103 / Chapter 10.1 --- Intelligent Front-End --- p.103 / Chapter 10.2 --- On Connection Method --- p.104 / Chapter 10.3 --- Many-Sorted Calculus --- p.104 / Chapter 11 --- CONCLUSION --- p.107 / APPENDICES / Chapter A --- COMPARISON OF SEMANTIC DATA MODELS --- p.110 / Chapter B --- CONSTRUCTION OP OCCURRENCES --- p.111 / Chapter C --- SYNTAX OF DDL FOR THE SCHEMA --- p.113 / Chapter D --- SYNTAX OF SEMANTIC MANIPULATION LANGUAGE --- p.116 / Chapter E --- TESTING SCHEMA FOR FUND INVESTMENT DBMS --- p.118 / Chapter F --- TESTING SCHEMA FOR STOCK INVESTMENT DBMS --- p.121 / Chapter G --- CONNECTION METHOD --- p.124 / Chapter H --- COMPARISON BETWEEN RESOLUTION AND CONNECTION METHOD --- p.128 / REFERENCES --- p.132

Thesis (M.Sc.)--York University, 2003. Graduate Programme in Computer Science. / Typescript. Includes bibliographical references (leaves 224-226). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL:http://gateway.proquest.com/openurl?url%5Fver=Z39.88-2004&res%5Fdat=xri:pqdiss&rft%5Fval%5Ffmt=info:ofi/fmt:kev:mtx:dissertation&rft%5Fdat=xri:pqdiss:MQ99307

Thesis (Ph.D)--Stanford University, 1999. / Title from pdf t.p. (viewed Mar. 27, 2002). "September 1998." "Adminitrivia V1/Prg/20000726"--Metadata.

Relational database systems have successfully solved many business data processing problems. The primary reason of this success is that the relational data model provides a simple, yet flexible view of data as tables. In studying VLSI/CAD data, we noticed that they are often represented in formats similar to relational tuples. Therefore, they can be stored easily in relational tables. However, it is generally agreed that conventional relational database systems are inefficient for VLSI/CAD applications, since such applications often access large amounts of data repetitively. In order to solve this problem, we designed and implemented a data mapping subsystem that converts VLSI/CAD data stored in relational tables into internal data structures so that they can be efficiently manipulated in C. By using our data mapping language, we could reduce the amount of code required by the data-structure construction parts of some real VLSI/ CAD tools to about 1/10 of that required by C implementation. Our data-structure builder consumes several times more CPU cycles. / Graduation date: 1991