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November Edition 2021

International Journal of Applied Information Systems solicits high quality original research papers for the November 2021 Edition of the journal. The last date of research paper submission is October 15, 2021.

A Question Classification in Closed Domain Question-Answer Systems

Jéferson N. Soares, Haniel G. Cavalcante, José E.B. Maia in Information Sciences

International Journal of Applied Information Systems
Year of Publication:2021
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors:Jéferson N. Soares, Haniel G. Cavalcante, José E.B. Maia
10.5120/ijais2021451913
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  1. Haniel Cavalcante G Jferson N. Soares and Jos E B Maia. A Question Classification in Closed Domain Question-Answer Systems. International Journal of Applied Information Systems 12(38):1-5, July 2021. URL, DOI BibTeX

    @article{10.5120/ijais2021451913,
    	author = "Jferson N. Soares, Haniel G. Cavalcante and Jos E.B. Maia",
    	title = "A Question Classification in Closed Domain Question-Answer Systems",
    	journal = "International Journal of Applied Information Systems",
    	issue_date = "July 2021",
    	volume = 12,
    	number = 38,
    	month = "July",
    	year = 2021,
    	issn = "2249-0868",
    	pages = "1-5",
    	url = "http://www.ijais.org/archives/volume12/number38/1120-2021451913",
    	doi = "10.5120/ijais2021451913",
    	publisher = "Foundation of Computer Science (FCS), NY, USA",
    	address = "New York, USA"
    }
    

Abstract

A Question-Answer System (QAS) is a Natural Language Processing (NLP) application whose purpose is to answer questions from users by consulting one or more available knowledge bases. Classifying the question posed by a user in a class of a predetermined set has risks and advantages. On the one hand, the correct classification reduces the scope of the search for the answer, generally resulting in more correct answers and greater processing efficiency of the QAS; on the other hand, an error in the classification reduces the chances of the system recovering from this error in the later stages of processing, thus resulting, almost always, in unsatisfactory responses. This work develops and evaluates a question classification scheme for Closed Domain QAS. The experiments showed that the approaches described for defining class and question classification can be used successfully in QAS based on closed collections of documents.

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Keywords

Question Classification, Question-Answer System, Closed Document Collection, Information Retrieval