Application of Emotional Analytics and Rule-Based Intelligence for Personalized Career and Life Guidance

@article{1715685,
      author = {R. Ruthra, K. Maniraj},
      title = {Application of Emotional Analytics and Rule-Based Intelligence for Personalized Career and Life Guidance},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {9},
      pages = {2765-2772},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1715685.pdf},
      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.},
      month = {March},
      doi = {https://doi.org/10.64388/IREV9I9-1715685}
  }