Conference proceeding
Answer Diversification for Complex Question Answering on the Web
ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PT I, PROCEEDINGS, v 6118(1), pp 375-382
01 Jan 2010
Abstract
We present a novel graph ranking model to extract a diverse set of answers for complex questions via random walks over a negative-edge graph. We assign a negative sign to edge weights in an answer graph to model the redundancy relation among the answer nodes. Negative edges can be thought of as the propagation of negative endorsements or disapprovals which is used to penalize factual redundancy. As the ranking proceeds, the initial score of the answer node, given by its relevancy to the specific question, will be adjusted according to a long-term negative endorsement from other answer nodes. We empirically evaluate the effectiveness of our method by conducting a comprehensive experiment on two distinct complex question answering data sets.
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Details
- Title
- Answer Diversification for Complex Question Answering on the Web
- Creators
- Palakorn Achananuparp - Drexel UniversityXiaohua Hu - Drexel UniversityTingting He - Central China Normal UniversityChristopher C. Yang - Drexel UniversityYuan An - Drexel UniversityLifan Guo - Drexel University
- Contributors
- M J Zaki (Editor)J X Yu (Editor)B Ravindran (Editor)Pudi (Editor)
- Publication Details
- ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PT I, PROCEEDINGS, v 6118(1), pp 375-382
- Series
- Lecture Notes in Artificial Intelligence
- Publisher
- Springer Nature
- Number of pages
- 3
- Grant note
- B07042 / Program of Introducing Talents of Discipline to Universities (China) IIS 0448023; NSF CCF 0905291; NSF IIP 0934197; NSFC 90920005 / NSF; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000281629200038
- Scopus ID
- 2-s2.0-79956306231
- Other Identifier
- 991019170505704721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Artificial Intelligence
- Computer Science, Information Systems
- Computer Science, Theory & Methods