Enabling experts to build knowledge bases from science textbooks

ABSTRACT

The long-term goal of Project Halo is to build an application called Digital Aristotle that can answer questions on a wide variety of science topics and provide user- and domain-appropriate explanations. As a near-term goal, we are focusing on enabling subject matter experts (SMEs) to construct declarative knowledge bases (KBs) from 50 pages of a science textbook in the domains of Physics, Chemistry, and Biology in a way that the system can answer questions similar to those in an Advanced Placement (AP) exam in the respective discipline. The textbook knowledge is a mixture of textual information, mathematical equations, tables, diagrams, and domain-specific representations such as chemical reactions. In this paper, we explore the following question: Can we build a knowledge capture system to enable SMEs to construct KBs from the knowledge found in science textbooks and use the resulting KB for deductive question answering? We answer this question in the context of a system called AURA that supports knowledge capture from science textbooks.

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems

General Terms:
Algorithms, Human Factors, Languages, Performance

Keywords:
concept, equations, tables, text book knowledge