학술논문

Designed Framework for Advanced Intelligent Job Recommendation System
Document Type
Conference
Source
2023 OITS International Conference on Information Technology (OCIT) Information Technology (OCIT), 2023 OITS International Conference on. :880-885 Dec, 2023
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Signal Processing and Analysis
Machine learning algorithms
Employment
Machine learning
Transforms
History
Information technology
Recommender systems
Job recommendation
Topic modeling
classification
TruncatedSVD
Language
Abstract
The Intelligent Job Recommendation System matches job searchers with possible jobs that match their profile using cutting-edge algorithms and machine learning techniques. The system gathers information about job applicants, such as their educational history, professional experience, and talents, and utilizes this data to create a thorough profile. Additionally, the system gathers data about open positions from numerous job sites and firm career pages. The system uses this data and a matching algorithm to suggest the job vacancies that will best suit the job searchers. The System’s goal is to make the job search process better for both businesses and job seekers. Receiving personalized job suggestions may save time for job searchers, and it can help companies find applicants who are more likely to meet their hiring needs. Based on subject matches, the recommendation algorithm provides a chart showing how the CV corresponds with the other employment vacancy. Hopefully, the chart offers some kind of justification. Our Intelligent Job Recommendation System is a ground-breaking method that identifies qualified applicants using AI and machine learning. By increasing the efficacy and efficiency of the job search process, the system has the potential to completely transform the employment market.