Suresh, Sathish Omega (2023) Employee Mental Health Recommendation Chatbot using NLP. Masters thesis, Dublin, National College of Ireland.
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Abstract
The mental health of employees has a significant impact on their wellbeing, which may also have an impact on their productivity and overall happiness at work. Nevertheless, there are a variety of reasons why employees can be reluctant to request help or support. We propose a chatbot-based strategy to address this issue by providing cosine similarity-based personalized mental health support to workers. The chatbot’s goal is to engage in natural language conversations with employees while providing useful information and guidance in response to their inquiries. The chatbot system is composed of two main methodologies: a text classification based on employee questions using the fine tuned BERT algorithm and a counselling-related instance based on emotions that makes use of similarity algorithm to connect queries from employees with the most appropriate emotion-based counseling responses. The system uses a natural language processing (NLP) model that has already been trained to extract the key components of the user’s query, identify the emotions in the question texts, and compare them to a database of emotional reactions connected to mental health. The system then suggests to the staff the most associated counseling responses determined by similarity scores.
Item Type: | Thesis (Masters) |
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Supervisors: | Name Email Menghwar, Teerath Kumar UNSPECIFIED |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science P Language and Literature > P Philology. Linguistics > Computational linguistics. Natural language processing H Social Sciences > HD Industries. Land use. Labor > Issues of Labour and Work > Health and Safety at Work. R Medicine > RA Public aspects of medicine > RA790 Mental Health |
Divisions: | School of Computing > Master of Science in Data Analytics |
Depositing User: | Tamara Malone |
Date Deposited: | 08 Jan 2025 16:32 |
Last Modified: | 08 Jan 2025 16:32 |
URI: | https://norma.ncirl.ie/id/eprint/7281 |
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