Job Portal

Abstract

Traditional Job Portals often struggle with inefficiencies, leading to mismatches between can- didates and employers. To solve this, we developed an intelligent Job Portal with an NLP-based career guidance Chatbot and a Resume Builder to streamline the job search process. Our sys- tem employs a deterministic rule-based approach using dynamic SQL query generation to analyze user-provided skills and match them with job descriptions through Boolean OR-based keyword matching, ensuring transparent and explainable recommendations. By assessing key factors like skills and job requirements, the platform generates tailored suggestions without relying on ma- chine learning models.The system also features a JavaScript-based Resume Builder, allowing users to create professional resumes with customizable templates, real-time formatting suggestions, and industry-specific keyword recommendations. The career Chatbot is powered by BERT (Bidirec- tional Encoder Representations from Transformers), specifically the MiniLM-L6-v2 model, which leverages cosine similarity for context-aware semantic matching against a curated Questions and answers dataset, enabling human-like interactions for career guidance.Users can interactively in- put their details, receive dynamically generated job suggestions, and ask career-related questions in real time. This system enhances job-matching accuracy through deterministic rule-based fil- tering, reduces hiring time via automated skill-to-job alignment, and improves user experience with intuitive tools. By combining transparent rule-based recommendations with advanced NLP- driven conversational assistance, our platform offers a modern yet interpretable approach to career guidance and recruitment, making job searching smarter and more efficient while maintaining full control over matching logic.