Title
A Knowledge Preservation And Re-Use Tool Based On Context-Driven Reasoning
Abstract
This article describes a knowledge preservation and re-use tool designed to capture the knowledge of a specific individual at the US National Science Foundation, for later retrieval by successors after his retirement. The system is designed in a Q&A format, where it is sufficiently intelligent to ask for clarifying questions. The primary objective was to create a system that would result in acceptance of the system by the users. The domain of interest to be preserved and re-used was programmatic knowledge about the NSF Industry/University Collaborative Research Centers (I/UCRC) Program, and more specifically, the knowledge of its long-time director, Dr. Alex Schwarzkopf. The system is called AskAlex and it uses a trio of techniques to accomplish its objectives. Contextual graphs (CxG) are used as the basic knowledge representation structure. CxG's are assisted by a search engine and an ontology of terms to help find the proper contextual graph that can best answer the question being asked. Evaluations with users and potential users generally confirm our selection and provided some guidance for improvements in the system.
Year
DOI
Venue
2015
10.1142/S0218213015500207
INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS
Keywords
Field
DocType
Knowledge preservation, knowledge re-use, contextual graphs, user interaction, Q&A systems
Body of knowledge,Ontology,Graph,Knowledge representation and reasoning,Ask price,Computer science,Knowledge-based systems,Artificial intelligence,Machine learning,Open Knowledge Base Connectivity
Journal
Volume
Issue
ISSN
24
5
0218-2130
Citations 
PageRank 
References 
1
0.36
20
Authors
6
Name
Order
Citations
PageRank
Avelino J. Gonzalez120442.36
Brian Sherwell210.36
Johann Nguyen310.36
Brian C. Becker410.36
Victor Chou Hung561.20
Patrick Brézillon6976107.14