Name
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. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/ICTAI.2009.108 | ICTAI |
Keywords | Field | DocType |
large knowledge-bases,simple heuristics,improved performance,problem solver,knowledge base,scalable problem-solver,advanced placement exam,domain expert,particular knowledge base,knowledge based system,data mining,advanced placement,knowledge based systems,acceleration,biology,advanced placement exams,question answering,cognition,reasoning | Question answering,Computer science,Knowledge-based systems,Theoretical computer science,Heuristics,Artificial intelligence,Knowledge base,Solver,Advanced Placement exams,Machine learning,Scalability | Conference |
ISSN | Citations | PageRank |
1082-3409 | 1 | 0.44 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shaw Yi Chaw | 1 | 142 | 12.39 |
| Ken Barker | 2 | 834 | 83.23 |
| Bruce Porter | 3 | 316 | 30.66 |
| dan g tecuci | 4 | 131 | 12.84 |
| Peter Z. Yeh | 5 | 380 | 28.42 |