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Research Interests
Porter's research addresses the grand challenge in Artificial Intelligence of building knowledge bases containing the accumulated understanding of entire fields of human inquiry, such as cell biology or global warming. These knowledge bases are quite unlike digital libraries, in which knowledge is represented as text and computers can do little more than recite information to people. In contrast, they use machine-sensible representations appropriate for automated reasoning and explanation generation. Porter's recent projects focus on knowledge representation, automated reasoning and knowledge acquisition.
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Selected Publications
(with Clark, P.) "Building Concept Representations from Components", Proceedings of the National Conference on Artificial Intelligence, pp. 369-376, 1997
(with Barker, K., et.al.) "Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned", Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI 2007)
(with Yeh, P. and Barker, K.) "A Unified Knowledge Based Approach for Sense Disambiguation and Semantic Role Labeling", Proceedings of the Twenty-First National Conference on Artificial Intelligence (AAAI 2006).
(with Barker, K., et.al.), "A Question-Answering System for AP Chemistry: Assessing KRR Technologies", The Ninth International Conference on the Principles of Knowledge Representation and Reasoning (KR2004).
(with Barker, K. and Clark, P.), "A Library of Generic Concepts for Composing Knowledge Bases", First International Conference on Knowledge Capture, October 21-23, 2001.
Books
(with van Harmelen, F. and Lifschitz, V., editors) Handbook of Knowledge Representation, in the Foundations of ArtificialI ntelligence series, Elsevier, 2008.
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- Best Paper Award, National Conference on Artificial Intelligence (AAAI)
- Recipient of the College of Natural Sciences Teaching Excellence Award
- Recipient of a Presidential Young Investigator Award by the National Science Foundation
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