CodeUP: A Web Application for Collaborative Question-answering System

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Yashi Agarwal 1 P. Raghu Vamsi 1,* Siddhant Jain 1 Jayant Goel 1

1. Jaypee Institute of Information Technology, A-10, Sector 62, NOIDA, India

* Corresponding author.


Received: 1 Sep. 2022 / Revised: 13 Jan. 2023 / Accepted: 26 May 2023 / Published: 8 Aug. 2023

Index Terms

BERT, Collaborative Learning, Deep Learning Models, Electra, Knowledge Sharing, Natural Language Processing, Universal Sentence Encoder, Software Module, Question Answer


The majority of collaborative learning and knowledge sharing (CLKS) platforms are built with numerous communication mediums, team and task management in mind. However, with the CLKS, the Question-Answering (QAs), User profile evaluation based on the quality of answers provided, and feeding of subject or project relevant data are all available. QAs are required for online or offline cooperation between team members or users. To that purpose, this paper presents a web application called CodeUP with features like QA system, Question similarity testing, and user profile rating for boosting communication and cooperation efficiency in CLKS for academic groups and small development teams. CodeUP is intended to be quickly established and step for academic or development groups to collaborate. As the CodeUP application supports the CLKS, it is also an ideal tool for academia and development teams to perform computer supported QA system and knowledge sharing in the sphere of work or study.

Cite This Paper

Yashi Agarwal, P. Raghu Vamsi, Siddhant Jain, Jayant Goel, "CodeUP: A Web Application for Collaborative Question-answering System", International Journal of Information Technology and Computer Science(IJITCS), Vol.15, No.4, pp.33-49, 2023. DOI:10.5815/ijitcs.2023.04.04


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