Application of Emotional Analytics and Rule-Based Intelligence for Personalized Career and Life Guidance
Abstract
This paper presents the Career Finance Platform, a full-stack web application built using Vanilla JavaScript on the frontend and an Express.js/SQLite backend, designed as a comprehensive system that consolidates career guidance, job discovery, course learning, career road mapping, and financial planning into a single authenticated user experience. The platform implements a token-based authentication system using bcrypt.js for secure credential management, a dynamic dashboard that aggregates applied jobs and enrolled courses, and a structured RESTful API covering fourteen endpoints across six functional domains. A dark-themed glass morphic UI delivers a modern, consistent user experience across all modules. Experimental evaluation confirms complete API route coverage across all six route groups and reliable sub-120 server response times.
Keywords
Vanilla JavaScript, Career Platform, SQLite, Node.js, Express.js, Bearer Token Authentication, bcrypt.js, Job Portal, Course Management, Career Roadmap, Finance Tools, RESTful API, Full-Stack Web Application, Glass morphic UI.
Citations
IRE Journals:
R. Ruthra, K. Maniraj "Application of Emotional Analytics and Rule-Based Intelligence for Personalized Career and Life Guidance" Iconic Research And Engineering Journals Volume 9 Issue 9 2026 Page 2765-2772 https://doi.org/10.64388/IREV9I9-1715685
IEEE:
R. Ruthra, K. Maniraj
"Application of Emotional Analytics and Rule-Based Intelligence for Personalized Career and Life Guidance" Iconic Research And Engineering Journals, 9(9) https://doi.org/10.64388/IREV9I9-1715685
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