Answering definition questions using web knowledge bases

Authors:
Zhushuo Zhang;Yaqian Zhou;Xuanjing Huang;Lide Wu
Affiliations:
Department of Computer Science and Engineering, Fudan University, Shanghai, China;Department of Computer Science and Engineering, Fudan University, Shanghai, China;Department of Computer Science and Engineering, Fudan University, Shanghai, China;Department of Computer Science and Engineering, Fudan University, Shanghai, China
Venue:
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Year:
2005

Citing 2
Cited 6

Term-weighting approaches in automatic text retrieval

Information Processing and Management: an International Journal
Evaluating answers to definition questions

NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2

Using multiple combined ranker for answering definitional questions

AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
An automatic definition extraction in Arabic language

NLDB'10 Proceedings of the Natural language processing and information systems, and 15th international conference on Applications of natural language to information systems
How to extract Arabic definitions from the web? Arabic definition question answering system

NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
A web knowledge based approach for complex question answering

AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Can click patterns across user's query logs predict answers to definition questions?

EACL '12 Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics
Contextual Language Models For Ranking Answers To Natural Language Definition Questions

Computational Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a definition question answering approach, which is capable of mining textual definitions from large collections of documents. In order to automatically identify definition sentences from a large collection of documents, we utilize the existing definitions in the Web knowledge bases instead of hand-crafted rules or annotated corpus. Effective methods are adopted to make full use of Web knowledge bases, and they promise high quality response to definition questions. We applied our system in the TREC 2004 definition question-answering task and achieved an encouraging performance with the F-measure score of 0.404, which was ranked second among all the submitted runs.