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Dissertation Information for Suk-Chung Yoon

NAME:
- Suk-Chung Yoon

DEGREE:
- Ph.D.

DISCIPLINE:
- Computer Science

SCHOOL:
- Northwestern University (USA) (1991)

ADVISORS:
- None

COMMITTEE MEMBERS:
- None

MPACT Status: Incomplete - Not_Inspected

Title: Strategies for design and implementation of an intelligent general-purpose knowledge base management system

Abstract: In recent years, there has been a growing interest that such seemingly disparate fields as database, artificial intelligence and logic programming are related in many ways. Expert systems in artificial intelligence, database management systems and logic programming are technologies that have evolved in parallel, but are now beginning to merge together toward the common goal of knowledge base management systems.

A major reason for merging these technologies is the realization of the systems that have significant improvements in productivity and functionality. The resulting system will benefit from the deductive problem solving capability and reasoning of expert systems based on semantic theories of information and the expressive power of logic programming as well as the sophisticated and efficient management of a large database of facts and enforcement of data reliability, integrity and security in database systems based on computational theories for efficient processing. Other important advantages of merging these technologies include enhanced query language, semantic query processing and optimization, intelligent user interface, etc.

Among the numerous research issues in knowledge base management systems, we propose a general strategy for design and implementation of an intelligent general-purpose knowledge base management system. In our proposed system, we can improve performance by providing intelligent answers. Database systems have been designed to effectively find all answers to queries. On the other hand, expert systems traditionally have been used to find a few good answers for a query. Our approach develops efficient strategies for supporting both classes of queries.

We develop a classification of certain kinds of knowledge applicable to knowledge base management systems containing both rule bases and databases. We suggest algorithms to utilize various kinds of semantic knowledge efficiently, including integrity constraints and heuristics (domain specific knowledge and expert knowledge), for answering queries. An important task is to use this knowledge selectively to keep the performance within a reasonable cost. So, we suggest control strategies(general strategies and heuristic based strategies) that identify relevant and profitable knowledge for a given query.

We address the efficient query evaluation strategies, optimization and search strategies based on the heuristic methods. So, we improve performance by reducing query processing time. Our proposed system has more intelligent and efficient search techniques for query processing than current systems.

MPACT Scores for Suk-Chung Yoon

A = 0
C = 1
A+C = 1
T = 0
G = 0
W = 0
TD = 0
TA = 0
calculated 2008-07-06 20:21:15

Advisors and Advisees Graph