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Abstract

This report includes the compiled papers from the 1st International Conference on Knowledge Capture held 21-23 Oct 2001 and sponsored by AFOSR. In today's Web-linked and data-rich world, there is a growing need to manage burgeoning amounts of information effectively. Although indexing and linking documents and other information sources is an important step, capturing the knowledge contained within these diverse sources is crucial for the effective use of large information repositories. Knowledge acquisition has been a challenging area of research in artificial intelligence, with its roots in early work to develop expert systems. Driven by the modern Internet culture and by knowledge-based industries, the study of knowledge acquisition has a renewed importance. Although there has been considerable work in the area of knowledge capture, activities have been distributed across several distinct research communities. In machine learning, learning apprentices acquire knowledge by non-intrusively watching a user perform a task. In the human-computer interaction community, programming-by-demonstration systems learn to perform a task by watching a user demonstrate how to accomplish it. In knowledge engineering, modeling techniques and design principles have been proposed for knowledge-based systems, often exploiting commonly occurring domain-independent inference structures and reusable domain-specific ontologies. In planning and process management, mixed-initiative systems acquire knowledge about a user's goals by taking commands or accepting advice regarding a task. In natural language processing, tools can process text and create representations of its knowledge content. All of these approaches are related in that they acquire information and organize it in knowledge structures that can be used for reasoning. They are complementary in that they use different techniques and approaches to capture different forms of knowledge.

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Document Details

Document Type
Technical Report
Publication Date
Mar 21, 2002
Accession Number
ADA403428

Entities

People

  • Yolanda Gil

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Autonomy
  • C4I
  • Engineered Resilient Systems
  • Ground and Sea Platforms
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Intelligence Software
  • Automata Theory
  • Cognitive Science
  • Computational Science
  • Computer Languages
  • Computer Programming
  • Computer Science
  • Computers
  • Electronic Mail
  • Health Services
  • Information Science
  • Information Systems
  • Medical Personnel
  • Natural Language Processing
  • Network Science
  • Ontologies

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Artificial Intelligence
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Information Retrieval