International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Combating Online Job Scams Using a Multi-Algorithm Ensemble-Based AI Detection System |
|---|---|
| ABSTRACT | In addition to increasing employment prospects, the quick expansion of internet job portals has led to a surge in fraudulent job ads. This project introduces a Fake Job Detection System based on Artificial Intelligence (AI) that automatically detects bogus job postings. Optical Character Recognition (OCR)-based picture extraction, Uniform Resource Locator (URL), and text input are all accepted by the system. Text preprocessing and feature extraction are done using Natural Language Processing (NLP) methods and Term Frequency–Inverse Document Frequency (TF-IDF). Additionally, fraud indications including money demands, exaggerated salary, and urgent language are identified by a rule-based engine. Long Short-Term Memory (LSTM), Random Forest, and Logistic Regression models are used to analyze the generated data. To increase accuracy and dependability, an ensemble learning technique is used to provide the final forecast. Through a Flask web application, the system gives real-time prediction with an accuracy of about 98%. Additionally, Streamlit is used to deploy the solution on Snowflake for scalable cloud accessibility. This study shows how deep learning (DL), machine learning (ML), and artificial intelligence (AI) may successfully shield people from online recruiting frauds. |
| AUTHOR | PALAKURI SWAMY, DR. P. SAMMULAL Post Graduate Student, Department of Computer Science and Engineering(Data Science), Jawaharlal Nehru Technological University, Hyderabad, India Professor, Department of Computer Science and Engineering, Jawaharlal Nehru Technological University, Hyderabad, India |
| VOLUME | 185 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1406058 |
| pdf/58_Combating Online Job Scams Using a Multi-Algorithm Ensemble-Based AI Detection System.pdf | |
| KEYWORDS | |
| References | 1. R. Gopi et al., "Fake Job Post Detection Using Machine Learning: An ADASYN Approach", 2025. 2. Ahamed Khalifa Z. et al., "Online Recruitment Fraud Detection", 2022. 3. Natasha Akram et al., "Online Recruitment Fraud Detection Using Deep Learning Approaches", 2024. 4. Jyoti Fating et al., "Fake Job Listing Detection Using Machine Learning Approach", 2023. 5. Varma Pranay et al., "Fake Job Recruitment Detection Using Machine Learning", 2020. 6. Dhruvil Ranparia et al., "Fake Job Prediction Using Sequential Network", 2024. 7. Shri Udayshankar et al., "Fake Job Post Prediction Using Data Mining", 2023. |
