Conference proceeding
AskDragon: A Redundancy-Based Factoid Question Answering System with Lightweight Local Context Analysis
JCDL 09: PROCEEDINGS OF THE 2009 ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES, pp.483-483
01 Jan 2009
Abstract
We introduce our QA system Ask Dragon 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.
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Details
- Title
- AskDragon: A Redundancy-Based Factoid Question Answering System with Lightweight Local Context Analysis
- Creators
- Xiaohua Zhou - Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USAPalakorn Achananuparp - Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USAE. K. ParkXiaohua Hu - Drexel UniversityXiaodan Zhang - Drexel Univ, Coll Informat Sci & Technol, Philadelphia, PA 19104 USAACM
- Publication Details
- JCDL 09: PROCEEDINGS OF THE 2009 ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES, pp.483-483
- Conference
- JCDL 09: 2009 ACM/IEEE JOINT CONFERENCE ON DIGITAL LIBRARIES
- Series
- ACM-IEEE Joint Conference on Digital Libraries JCDL
- Publisher
- Assoc Computing Machinery
- Number of pages
- 1
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science (Informatics)
- Identifiers
- 991019170506004721
InCites Highlights
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- Web of Science research areas
- Computer Science, Hardware & Architecture
- Computer Science, Information Systems