NDLI: Extracting answers to natural language questions from large-scale corpus

Content Provider	IEEE Xplore Digital Library
Author	Peng Li Xiao Long Wang Yi Guan Yu Ming Zhao
Copyright Year	2005
Description	Author affiliation: Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., China (Peng Li; Xiao Long Wang; Yi Guan; Yu Ming Zhao)
Abstract	This paper provides a novel and tractable method for extracting exact textual answers from the returned documents that are retrieved by traditional IR system in large-scale collection of texts. In our approach, WordNet and Web information are employed to improve the performance as external auxiliary resources, then some NLP technologies are used to constitute the empirical answer ranking formula, such as POS tagging, Named Entity recognition, and parser etc. The method involves automatically ranking passages with System Similarity Model, automatically downloading related Web pages by means of Web crawler, and automatically mining answers with empirical formula from candidate answer sets. The series of experimental results show that the overall performance of our system is good and the structure of the system is reasonable.
Starting Page	690
Ending Page	694
File Size	2408377
Page Count	5
File Format	PDF
ISBN	0780393619
DOI	10.1109/NLPKE.2005.1598824
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-30
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Natural languages Moon Crawlers Web pages Tagging Information retrieval Natural language processing Large-scale systems Data mining
Content Type	Text
Resource Type	Article

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