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Evolution of Techniques for Question Answering over Knowledge Base: A Survey

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2020
Authors:
Ashish Salunkhe
10.5120/ijca2020919817

Ashish Salunkhe. Evolution of Techniques for Question Answering over Knowledge Base: A Survey. International Journal of Computer Applications 177(34):9-14, January 2020. BibTeX

@article{10.5120/ijca2020919817,
	author = {Ashish Salunkhe},
	title = {Evolution of Techniques for Question Answering over Knowledge Base: A Survey},
	journal = {International Journal of Computer Applications},
	issue_date = {January 2020},
	volume = {177},
	number = {34},
	month = {Jan},
	year = {2020},
	issn = {0975-8887},
	pages = {9-14},
	numpages = {6},
	url = {http://www.ijcaonline.org/archives/volume177/number34/31120-2020919817},
	doi = {10.5120/ijca2020919817},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

In this paper, a brief study of the advancements in the Question Answering domain as a type of information retrieval system is presented. Question Answering systems are responsible to provide answers to the questions proposed over a knowledge base in natural language to retrieve the required information. The promising results achieved in Question Answering in Natural Language Processing are discussed. The aim is to cover a concise yet complete understanding of the advances in Question Answering Systems classified based on domain and question type and brief information about metrics used to evaluate the system.

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Keywords

Data mining, text mining, question answering, classification, named entity recognition, neural networks, pos tagging