Improving database performances in a changing environment with uncertain and dynamic information demand: An intelligent database system approach
Date of Completion
January 1999
Keywords
Business Administration, General|Information Science|Artificial Intelligence
Degree
Ph.D.
Abstract
The purpose of this dissertation is to explore an alternative way to improve the performance of a relational database system for information retrieval while facing dynamic complex queries and changing system environments. While past research focuses on how to efficiently and quickly process individual information-retrieval queries without considering changes in query patterns and system congestion conditions, existing relational databases are very likely to suffer performance deterioration. We propose an Intelligent Database System (IDS) that is capable of dynamically restructuring a relational database to adapt to changes. ^ The ultimate goal of an IDS is to provide timely query response and satisfactory database information-retrieval performance. To achieve the objective of an IDS, we develop a sequence of methodologies to classify queries of different complexity levels, identify high-performance robust database structures, consider system congestion conditions, and detect query patterns. We conduct laboratory experiments and use them to demonstrate and partially validate our methodologies. Experiment results and these methodologies are also used to illustrate the effectiveness and potential benefit of an IDS. ^
Recommended Citation
Chen, Andrew Nai-Kuang, "Improving database performances in a changing environment with uncertain and dynamic information demand: An intelligent database system approach" (1999). Doctoral Dissertations. AAI9942566.
https://digitalcommons.lib.uconn.edu/dissertations/AAI9942566