World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
12769
World Ranking
13812
National Ranking
5485

Research.com Recognitions

  • 2008 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 1990 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI)

Overview

Douglas B. Lenat was affiliated with Stanford University in the United States. Their research spanned several areas within computer science and decision sciences, with a focus on artificial intelligence, management science and operations research, and information systems and management.

The main topics covered in their work included advanced graph neural networks, data quality and management, semantic web and ontologies, and scientific computing and data management.

Douglas B. Lenat published research articles in prominent venues such as AI Magazine and IEEE Annals of the History of Computing. Notable publications include:

  • Knowledge graphs: Introduction, history, and perspectives (2022, AI Magazine)
  • Knowledge Graphs: Introduction, History and, Perspectives (2022, AI Magazine)
  • Creating a 30-Million-Rule System: MCC and Cycorp (2022, IEEE Annals of the History of Computing)

The scientist frequently collaborated with the following coauthors:

  • Vinay K. Chaudhri
  • Chaitanya Baru
  • Naren Chittar
  • Michael Genesereth
  • James Hendler

They were recognized as a Fellow of the American Association for the Advancement of Science (AAAS) in 2008 and as a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 1990.

Best Publications

  • Building Expert Systems

    Frederick Hayes-Roth;Donald A. Waterman;Douglas B. Lenat

  • Building Large Knowledge-Based Systems: Representation and Inference in the Cyc Project

    Douglas B. Lenat;R. V. Guha

  • CYC: a large-scale investment in knowledge infrastructure

    Douglas B. Lenat

  • Knowledge-based systems in artificial intelligence

    Randall Davis;Douglas B Lenat

  • Building large knowledge-based systems

    Douglas Lenat;Ramanathan V. Guha

  • Cyc: toward programs with common sense

    Douglas B. Lenat;R. V. Guha;Karen Pittman;Dexter Pratt

  • Cyc: a mid-term report

    R. V. Guha;Douglas B. Lenat

  • CYC: a mid-term report

    R. V. Guha;Douglas B. Lenat

  • CYC: Using common sense knowledge to overcome brittleness and knowledge acquistion bottlenecks

    Doug Lenat;Mayank Prakash;Mary Shepherd

  • On the thresholds of knowledge

    Douglas B. Lenat;Edward A. Feigenbaum

  • Why AM an EUISKO appear to work.

    Douglas B. Lenat;John Seely Brown

  • AM, an artificial intelligence approach to discovery in mathematics as heuristic search

    Douglas Bruce Lenat

  • Eurisko: A program that learns new heuristics and domain concepts

    Douglas B. Lenat

  • Enabling agents to work together

    R. V. Guha;Douglas B. Lenat

  • The nature of heuristics

    Douglas B. Lenat

  • The Role of Heuristics in Learning by Discovery: Three Case Studies

    Douglas B. Lenat

  • Mapping Ontologies into Cyc

    Unknown

  • Searching for common sense: populating Cyc™ from the web

    Cynthia Matuszek;Michael Witbrock;Robert C. Kahlert;John Cabral

  • Automated theory formation in mathematics

    Douglas B. Lenat

  • Theory formation by heuristic search

    Douglas B. Lenat

  • The ubiquity of discovery

    Douglas B. Lenat

  • The ubiquity of discovery

    Douglas B. Lenat

  • BEINGs: knowledge as interacting experts

    Douglas B. Lenat

  • Beings: knowledge as interacting experts

    Douglas B. Lenat

  • A representation language language

    Russell Greiner;Douglas B. Lenat

  • On the thresholds of knowledge

    Douglas B. Lenat;Edward A. Feigenbaum

  • PRINCIPLES OF PATTERN-DIRECTED INFERENCE SYSTEMS

    Frederick Hayes-Roth;D.A. Waterman;Douglas B. Lenat

  • Building expert systems

    Frederick Hayes-Roth;Donald A. Waterman;Douglas B. Lenat

Frequent Co-Authors

Ramanathan V. Guha
Ramanathan V. Guha Google (United States)
Edward A. Feigenbaum
Edward A. Feigenbaum Stanford University
Bilge Mutlu
Bilge Mutlu University of Wisconsin–Madison
Benjamin Van Durme
Benjamin Van Durme Johns Hopkins University
Eric Horvitz
Eric Horvitz Microsoft (United States)
John Seely Brown
John Seely Brown Palo Alto Research Center
David E. Shaw
David E. Shaw D. E. Shaw Research
Roger Azevedo
Roger Azevedo University of Central Florida
Takayuki Kanda
Takayuki Kanda Kyoto University

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