STUDENT TALENT ANALYSIS
Introduction
It is of great importance that students at our university can easily find job opportunities best suited to their talents. For this purpose, we have developed the "Student Talent Analysis" system, which automatically identifies and recommends the most suitable job postings based on students’ departments, preferred city or cities to work in, and their social-technical skills. Our system aims to facilitate the job search process for students studying in relevant departments.
Initially, our system is designed to serve students in the departments of Computer Engineering, Electrical-Electronics Engineering, Industrial Engineering, Mechanical Engineering, and Management Information Systems.
By visiting the address https://kariyerpusulam.bakircay.edu.tr/, you can access the system.
Problem:
Currently, students manually follow job postings from various sources and have difficulty finding suitable job announcements. This situation leads to the following problems:
- Time Loss: Checking job postings individually across different platforms is time-consuming.
- Difficulty Finding Suitable Announcements: It is hard for students to filter job postings that exactly match their talents and preferred locations.
- Currency Issue: Tracking expired job postings can lead to misdirection.
Solution:
The “Student Talent Analysis” system we developed aims to eliminate these problems. The system regularly collects and analyzes job postings; it matches open and suitable announcements with the information provided by students and offers recommendations.
Thus:
- Students can easily reach the job postings that best fit their talents and preferences.
- The postings in the system are continuously updated, and only open applications are shown.
- The system continues to improve its recommendations by leveraging past data.
Features:
- Easy Access: You can easily access the system via the web and receive job recommendations by entering your profile information.
- Automatic Update and Data Collection: The system automatically collects and updates job postings at regular intervals.
- Smart Matching: Job postings are dynamically matched based on department, city preferences, and technical-social skill information.
- Technical Infrastructure: The system is developed using the Python programming language, and data is securely stored in a MySQL database.
- Continuous Learning: The system continuously improves its recommendation accuracy by learning from user interactions and new postings.
- Current and Passive Posting Management: Closed job postings are stored passively in the system but continue to be used in analysis and learning processes.
- With the “Student Talent Analysis” system, we aim to facilitate our students’ career journeys and help them access the right job opportunities faster. We believe this system will save students time during their job search and provide solutions tailored to their needs.