CareerCue: A Survey on Intelligent Job Recommendation Systems Using Skill Extraction and Conversational AI

Shreya Nayak , Vanipriya C.H.

Job Recommendation, Skill Extraction, CareerCue, Telegram Bot, Natural Language Processing, Artificial Intelligence, API Integration, Conversational Interfaces.

The fast growth of online job platforms has created a demand for smarter job recommendation systems that can offer personalized, accurate, and up-to-date job suggestions. Traditional systems that rely primarily on keyword matching often fail to understand the true meaning of user skills and preferences, leading to less relevant job matches. This survey reviews recent techniques and developments in this field, focusing on skill extraction, semantic matching, real-time job data integration, and interactive conversational interfaces like the CareerCue Telegram bot. The paper analyzes over twenty recent studies, highlighting methods such as hybrid filtering and natural language processing, and discusses challenges including platform limitations, cold start problems, transparency, and data privacy. Future directions like explainable AI and federated learning are also explored to improve the effectiveness and trustworthiness of job recommendation systems.

Published Paper   E-Certificate

"CareerCue: A Survey on Intelligent Job Recommendation Systems Using Skill Extraction and Conversational AI", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.10, Issue 8, page no.b689-b695, August-2025, Available :https://ijsdr.org/papers/IJSDR2508182.pdf

Volume 10 Issue 8, August-2025

Pages : b689-b695

Paper Reg. ID: IJSDR_304724

Published Paper Id: IJSDR2508182

Downloads: 000265

Research Area: Others area

Country: Bengaluru, Karnataka, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2508182

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2508182

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition