DocumentCode
2803453
Title
A Scalable Problem-Solver for Large Knowledge-Bases
Author
Chaw, Shaw-Yi ; Barker, Ken ; Porter, Bruce ; Tecuci, Dan ; Yeh, Peter Z.
Author_Institution
Dept. of Comput. Sci., Univ. of Texas at Austin, Austin, TX, USA
fYear
2009
fDate
2-4 Nov. 2009
Firstpage
461
Lastpage
468
Abstract
We describe a problem solver built to answer questions like those on advanced placement exams using knowledge bases authored by domain experts. The problem solver is designed to work independently of any particular knowledge base or domain. Given a question, the problem solver identifies those portions of the knowledge base that are relevant to the question. We found that simple heuristics for judging relevance significantly improved performance, with no drop in coverage.
Keywords
knowledge based systems; problem solving; advanced placement exams; large knowledge-bases; scalable problem-solver; Artificial intelligence; Biological cells; Cells (biology); Chemistry; Equations; Information retrieval; Libraries; Logic; Physics computing; Vents; Knowledge Base Systems; Problem Solving; Project Halo; Question Answering; Reasoning;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 2009. ICTAI '09. 21st International Conference on
Conference_Location
Newark, NJ
ISSN
1082-3409
Print_ISBN
978-1-4244-5619-2
Electronic_ISBN
1082-3409
Type
conf
DOI
10.1109/ICTAI.2009.108
Filename
5362564
Link To Document