Name
Title | ||
|---|---|---|
AskDragon: a redundancy-based factoid question answering system with lightweight local context analysis |
Abstract | ||
|---|---|---|
We introduce our QA system AskDragon which employs a novel lightweight local context analysis technique to handling two broad classes of factoid questions, entity and numeric questions. The local context analysis module dramatically improves the efficiency of QA systems without sacrificing high accuracy performance. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1555400.1555525 | JCDL |
Keywords | Field | DocType |
qa system askdragon,answer scoring,qa system,local context analysis module,high accuracy performance,broad class,lightweight local context analysis,novel lightweight local context,numeric question,redundancy-based approach,analysis technique,factoid question,question answering,local context analysis,answer generation,redundancy-based factoid question answering,question answering system | Question answering,Information retrieval,Computer science,Context analysis,Redundancy (engineering),Factoid | Conference |
ISSN | Citations | PageRank |
2575-7865 | 0 | 0.34 |
References | Authors | |
1 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaohua Zhou | 1 | 438 | 25.82 |
| Palakorn Achananuparp | 2 | 302 | 23.16 |
| E. K. Park | 3 | 233 | 9.92 |
| Xiaohua Hu | 4 | 2819 | 314.15 |
| Xiaodan Zhang | 5 | 25 | 8.37 |