“BOTBUTLER” A Question-answering System Against COVID-19 Information Overload

Dissanayake, Luckindu

dc.contributor.author	Dissanayake, Luckindu
dc.date.accessioned	2023-01-18T10:38:29Z
dc.date.available	2023-01-18T10:38:29Z
dc.date.issued	2022
dc.identifier.citation	Dissanayake, Luckindu (2022) “BOTBUTLER” A Question-answering System Against COVID-19 Information Overload. BSc. Dissertation, Informatics Institute of Technology	en_US
dc.identifier.issn	2018155
dc.identifier.uri	http://dlib.iit.ac.lk/xmlui/handle/123456789/1486
dc.description.abstract	The research highlights a popular problem in today's world; information overload in COVID-19. To overcome from the problem, the project discovers an attempt with the help of similarity matching technologies. The proposed solution is a web-based question answering system to answer COVID19 related questions in accurate way. The research also considers software aspects such as performance, usability, testability, and user interface aesthetics. A twitter question answering data source has been used throughout the project. The solution utilizes deep learning, natural language processing and cosine similarity to complete the mission.	en_US
dc.language.iso	en	en_US
dc.subject	Deep Learning	en_US
dc.subject	Vectorization	en_US
dc.subject	Question-answering	en_US
dc.title	“BOTBUTLER” A Question-answering System Against COVID-19 Information Overload	en_US
dc.type	Thesis	en_US