Project Help Chatbot

Authors

  • Sugandha Bhagwat Dept. of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India Author
  • S.S. Sridhar Professor, Dept. of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India Author

DOI:

https://doi.org/10.61841/gxsqa604

Keywords:

Machine Learning, NLP, AI, Deep Learning

Abstract

The growth of artificially trained machines such as chatbots are a major achievement in Computer Science. A Chatbot is a software that simulates the human behavior and carries out conversations in a human-like manner. It helps to analyze the opinions, emotions etc. that are exchanged by and between humans. Chatbots are considered to be a pseudo- human medium of interaction with a computer system or a software technology meant to make a user experience conversation with using artificial intelligence. The vast fields of Deep Learning and NLP toolkits have rendered engineers and scientists come up with creative applications of a chatbot to make life easier. This paper intends to introduce one ore unique application of chatbot which serves as a platform for the regular college students to find a perfect team for their projects. Students not only seem to face difficulty in choosing a team but also realizing the actual knowledge about the project they want to make. This chatbot gives just the right solution by matching the known skills using NLP pattern matching techniques to find the best suitable project with the required skill set. Students not only save time but also find suitable teammates with equally qualified knowledge.

In conclusion it will help to improve the efficiency of an individual as well as a team by contributing a helping hand to its members to lead them ti the success of their project.

 

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Published

31.10.2020

Issue

Vol. 24 No. 8 (2020): 24 (8) 2020

Section

Articles

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How to Cite

Bhagwat, S., & Sridhar, S. (2020). Project Help Chatbot. International Journal of Psychosocial Rehabilitation, 24(8), 1000-1006. https://doi.org/10.61841/gxsqa604