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.