Knowledge Representation & Reasoning
Webpage: http://www.cs.utexas.edu/users/mfkb/
Director: Bruce Porter
We develop methods for building and using large knowledge systems. Our research focuses on knowledge representation, automated reasoning, question answering and explanation generation. We have begun to explore ways of extracting knowledge from text.
People
Bruce Porter Faculty porter [at] cs utexas edu
Publications
     [Expand to show all 35][Minimize]
Knowledge integration across multiple texts 2009
Doo Soon Kim, Ken Barker, and Bruce Porter, In The Fifth International Conference on Knowledge Capture (KCAP2009) 2009.
A Scalable Problem-Solver for Large Knowledge-Bases 2009
S. Chaw, K. Barker, B. Porter, D. Tecuci, and Peter Yeh, In Proceedings of the 21st International Conference on Tools with Artificial Intelligence (ICTAI 2009) 2009.
Constructing a semantic interpreter using distributional analysis 2009
Michael Glass, Ken Barker, Rekha Kumar, Guhan Ravi and Bruce Porter, In Proceedings of the Eighth Conference of the Pacific Association for Computational Linguistics 2009.
Kleo: A Bootstrapping Learning-by-reading System 2009
Doo Soon Kim and Bruce Porter, In AAAI Spring Symposium on Learning by Reading and Learning to Read 2009.
Improving semantic integration by learning semantic interpretation rules 2008
Michael Glass and Bruce Porter, In AAAI Spring Symposium on Semantic Scientific Knowledge Integration 2008.
Integrating declarative knowledge: Issues, Algorithms and Future Work 2008
Doo Soon Kim and Bruce Porter, In AAAI Spring Symposium on Semantic Scientific Knowledge Integration 2008.
Handling Granularity Differences in Knowledge Integration 2007
Doo Soon Kim and Bruce Porter, In AAAI Fall Symposium on Computational Approaches to Representation Change during Learning and Development 2007.
Learning by Reading: A Prototype System, Performance Baseline and Lessons Learned 2007
Ken Barker, Bhalchandra Agashe, Shaw-Yi Chaw, James Fan, Noah Friedland, Michael Glass, Jerry Hobbs, Eduard Hovy, David Israel, Doo Soon Kim, Rutu Mulkar-Mehta, Sourabh Patwardhan, Bruce Porter, Dan Tecuci, and Peter Yeh, In Proceedings of the Twenty-Second National Conference on Artificial Intelligence (AAAI 2007) 2007.
A Unified Knowledge Based Approach for Sense Disambiguation and Semantic Role Labeling 2006
Peter Yeh, Bruce Porter, Ken Barker, In Proceedings of the Twenty-First National Conference on Artificial Intelligence 2006.
Indirect Anaphora Resolution as Semantic Path Search 2005
James Fan, Ken Barker, Bruce Porter, In Proceedings of Third International Conference on Knowledge Capture 2005.
Matching Utterances to Rich Knowledge Structures to Acquire a Model of the Speaker's Goal 2005
Peter Yeh, Bruce Porter, Ken Barker, In Proceedings of Third International Conference on Knowledge Capture 2005.
A Question-Answering System for AP Chemistry: Assessing KR&R Technologies 2004
Ken Barker, Vinay K. Chaudhri, Shaw Yi Chaw, Peter E. Clark, James Fan, David Israel, Sunil Mishra, Bruce Porter, Pedro Romero, Dan Tecuci, Peter Yeh, In The Ninth International Conference on the Principles of Knowledge Representation and Reasoning (KR2004) 2004.
Interpreting Loosely Encoded Questions 2004
James Fan, Bruce Porter, In Proceedings of the Nineteenth National Conference on Artificial Intelligence 2004.
Mining Transformation Rules for Semantic Matching 2004
Peter Yeh, Bruce Porter, Ken Barker, In Proceedings of ECML/PKDD 2nd International Workshop on Mining Graphs, Trees and Sequences (MGTS'04) 2004.
Project Halo: Towards a Digital Aristotle 2004
Noah S. Friedland, Paul G. Allen, Gavin Matthews, Michael Witbrock, David Baxter, Jon Curtis, Blake Shepard, Pierluigi Miraglia, Jürgen Angele, Steffen Staab, Eddie Moench, Henrik Oppermann, Dirk Wenke, David Israel, Vinay Chaudhri, Bruce Porter, Ken Barker, James Fan, Shaw Yi Chaw, Peter Yeh, Dan Tecuci, Peter Clark, Artificial Intelligence Magazine, Vol. 25, 4 (2004), pp. 29-47.
Towards a Quantitative, Platform-Independent Analysis of Knowledge Systems 2004
Noah S. Friedland, Paul G. Allen, Michael Witbrock, Gavin Matthews, Nancy Salay, Pierluigi Miraglia, Jurgen Angele, Steffen Staab, David Israel, Vinay Chaudhri, Bruce Porter, Ken Barker, Peter Clark, In The Ninth International Conference on the Principles of Knowledge Representation and Reasoning (KR2004) 2004.
The Knowledge Required to Interpret Noun Compounds 2003
James Fan, Ken Barker, Bruce Porter, In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence 2003.
Using Transformations to Improve Semantic Matching 2003
Peter Yeh, Bruce Porter, Ken Barker, In Second International Conference on Knowledge Capture, October 2003.
A Library of Generic Concepts for Composing Knowledge Bases 2001
Ken Barker, Bruce Porter, and Peter Clark, In Proceedings of First International Conference on Knowledge Capture, pp. 14-21 2001.
Representing Roles and Purpose 2001
James Fan, Ken Barker, Bruce Porter, Peter Clark, In First International Conference on Knowledge Capture, October 2001.
Automated Modeling of Complex Systems to Answer Prediction Questions 1997
J. Rickel and Bruce Porter, PhD Thesis, Department of Computer Sciences, University of Texas.
Building Concept Representations from Reusable Components. 1997
Peter Clark and Bruce Porter, In AAAI'97, pp. 369--376 1997. CA: AAAI Press. (Best Paper Award).
Developing and Empirically Evaluating Robust Explanation Generators: The KNIGHT Experiments 1997
James C. Lester, Bruce Porter, Computational Linguistics Journal, Vol. 23, 1 (1997), pp. 65--101.
Iterative Refinement of Knowledge Bases with Consistency Guarantees 1997
Stephen F. Correl and Bruce W. Porter , No other information
Using Access Paths to Guide Inference with Conceptual Graphs 1997
Peter Clark and Bruce Porter, In Proc Int Conf on Conceptual Structures - ICCS'97 (Lecture Notes in AI), D. lukose, H. Delugach, M. Keeler, L. Searle, J. Sowa (Eds.), Vol. 1257, pp. 521--535, Berlin, Germany 1997. Springer.
A Compositional Approach to Representing Planning Operators 1996
Peter Clark, Bruce Porter, and Don Batory , Technical Report AI06-331, University of Texas at Austin.
A Computational Model of Complex Concept Composition 1996
C. Andersen , Masters Thesis, Department of Computer Science, University of Texas at Austin.
Automated Modeling of Complex Systems for Answering Prediction Questions 1995
J. Rickel , PhD Thesis, Department of Computer Sciences, University of Texas at Austin.
Robust Natural Language Generation from Large-Scale Knowledge Bases 1995
Charles B. Callaway and James Lester, In Proceedings of the Fourth Bar-Ilan Symposium on the Foundations of AI 1995.
Analysis and Empirical Studies of Derivational Analogy 1994
B. Blumenthal and Bruce Porter, Artificial Intelligence Journal, Vol. 67, 2 (1994), pp. 287--328.
Automated Modeling for Answering Prediction Questions: Selecting the Time Scale and System Boundary 1994
J. Rickel and Bruce Porter , In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94), pp. 1191--1198, Cambridge, MA 1994. AAAI/MIT Press.
Extracting Viewpoints from Knowledge Bases 1994
Liane Acker and Bruce Porter , In Proceedings of the 12th National Conference on Artificial Intelligence, pp. 547-552 1994.
Rules and Precedents as Complementary Warrants 1991
K. Branting and Bruce Porter, In AAAI-91, pp. 3--9 1991.
Concept Learning and Heuristic Classification in Weak-Theory Domains 1990
R. Bareiss, Bruce Porter and R. Holte, Artificial Intelligence, Vol. 45 (1990), pp. 229-263.
Controlling Search for the Consequences of New Information during Knowledge Integration 1989
K. Murray and Bruce Porter , In Proceedings of the Sixth International Workshop on Machine Learning, pp. 290-295, Ithaca, NY, June 1989.
Projects
Machine Reading 2009 - Present
Project Halo 2003 - 2010
Rapid Knowledge Formation 1999 - 2003
The Botany Knowledge Base 1986 - 1994
Areas of Interest
Automated Modeling Case-Based Reasoning Knowledge Representation & Reasoning Knowledge-Base Access Natural Language Processing Supervised Learning
Software/Data
Component Library The cornerstone of our approach to building Knowledge Systems is the assembly of knowledge bases from reusable component... 2000
KM: The Knowledge Machine To encode our knowledge bases, we use the KM knowledge representation and reasoning system. KM is a powerful, frame-base...