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Reseach Article

Effective Question Answering Techniques and their Evaluation Metrics

by Jaspreet Kaur, Vishal Gupta
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 65 - Number 12
Year of Publication: 2013
Authors: Jaspreet Kaur, Vishal Gupta
10.5120/10978-6122

Jaspreet Kaur, Vishal Gupta . Effective Question Answering Techniques and their Evaluation Metrics. International Journal of Computer Applications. 65, 12 ( March 2013), 30-37. DOI=10.5120/10978-6122

@article{ 10.5120/10978-6122,
author = { Jaspreet Kaur, Vishal Gupta },
title = { Effective Question Answering Techniques and their Evaluation Metrics },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 65 },
number = { 12 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 30-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume65/number12/10978-6122/ },
doi = { 10.5120/10978-6122 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:20:59.078923+05:30
%A Jaspreet Kaur
%A Vishal Gupta
%T Effective Question Answering Techniques and their Evaluation Metrics
%J International Journal of Computer Applications
%@ 0975-8887
%V 65
%N 12
%P 30-37
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Question Answering (QA) is a focused way of information retrieval. Question Answering system tries to get back the accurate answers to questions posed in natural language provided a set of documents. Basically question answering system (QA) has three elements i. e. question classification, information retrieval (IR), and answer extraction. These elements play a major role in Question Answering. In Question classification, the questions are classified depending upon the type of its entity. Information retrieval component is used to determine success by retrieving relevant answer for different questions posted by the intelligent question answering system. Answer extraction module is growing topics in the QA in which ranking and validating a candidate's answer is the major job. This paper offers a concise discussion regarding different Question Answering types. In addition we describe different evaluation metrics used to evaluate the performance of different question answering systems. We also discuss the recent question answering systems developed and their corresponding techniques.

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Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Question Answering System Evaluation Metrics Information Retrieval