Adaptive ML Professional Advisor System
Abstract
Abstract In recent years, intelligent recommendation systems have gained significant attention in career guidance applications. This paper proposes an AI-Based Adaptive Professional Recommendation System designed to overcome the limitations of static career advisory platforms. The system utilizes machine learning models to process multidimensional user data, including skills, interests, academic performance, and feedback. An adaptive learning mechanism enables the model to update recommendations dynamically, improving prediction accuracy with each interaction. The proposed framework offers a scalable and efficient solution for personalized career guidance. Keywords Career Recommendation, Artificial Intelligence, Machine Learning, Adaptive Systems, Student Career Guidance
Fields of Study & Subjects
Recommender Systems and Techniques
Edcuational Technology Systems
Online Learning and Analytics
Publication details
- Journal / source
- INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
- Volume
- 10
- Issue
- 03
- Pages
- 1–9
- Publication date
- 12 March 2026
- Language
- EN