STEP TOWARD THE NEXT GENERATION OF INFORMATION SYSTEMS

Award Information
Agency:
National Science Foundation
Branch
n/a
Amount:
$40,000.00
Award Year:
1985
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Award Id:
2651
Agency Tracking Number:
2651
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Technology Dr, 1000 Technology Pk Ctr, Knoxville, TN, 37932
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
GREGORY A HOLTON
RESEARCH SCIENTIST III
(615) 966-5232
Business Contact:
() -
Research Institute:
n/a
Abstract
PURPOSE: THE PROPOSED RESEARCH IS FOR DEVELOPING SPECIFICATIONS FOR AN INTELLIGENT DATA BASE MODEL THAT WILL BE THE BASIS FOR AN INTELLIGENT DATA BASE MANAGEMENT SYSTEM (IDBMS). REASONS FOR RESEARCH: INFORMATION NEEDS OF SYSTEM USERS FREQUENTLY CHANGE. EFFICIENT INFORMATION SYSTEMS MUST BE ABLE TO ACCOMODATE EVOLVING INFORMATION REQUIREMENTS; HOWEVER, AVAILABLE INFORMATION SYSTEMS PROVIDE LIMITED FEATURES FOR DYNAMIC MODIFICATION. METHODS PROPOSED: AN INTELLIGENT DATA BASE MODEL COMPRISED OF THREE MODULES IS PROPOSED. THESE MODULES ARE (1) A DATA MODEL DEFINER, (2) AN INTERPRETATION DEFINER, AND (3) A DATABASE/INTERPRETATION ORGANIZER. THE PROPOSED MODEL IS BASED ON THE ENTITY-RELATIONSHIP MODEL AND ON RESEARCH ON ARTIFICIAL INTELLIGENCE. SPECIFICATIONS FOR EACH MODULE WILL BE DEVELOPED USING THE MOST RECENT RESEARCH ON KNOWLEDGE REPRESENTATION. ANTICIPATED RESULTS: THE RESULT OF THIS WORK WILL BE SPECIFICATIONS FOR AN INTELLIGENT DATA BASE MODEL WHEREIN DATA ARE STORED AS ENTITIES THAT CAN BE SEMANTICALLY INTERPRETED OR RELATED, USING ADDITIONAL FACTS AND HEURISTICS IN THE KNOWLEDGE BASE TO DERIVE THE DESIRED INFORMATION. IMPLICATIONS OR RESEARCH: THE INTELLIGENT DATA BASE MODEL ISTHE FIRST STEP IN DEVELOPING AN IDBMS. IT WILL PROVIDE THE FRAMEWORK FOR INTELLIGENT INFORMATION RETRIEVAL VIA THE IDBMS. POTENTIAL APPLICATIONS: THE IDBMS IS A WAY TO PERFORM A KNOWLEDGE-BASED SEARCH OF DATA. IT CAN BE USED TO PROCESS ALMOST ALL FORMS OF DIVERSE DATA WHERE CAUSE-EFFECT RELATIONSHIPS ARE SOUGHT.

* information listed above is at the time of submission.

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