Introduction to the Laboratory
Overview
In our laboratory, we are conducting research on a web system aimed at supporting students' job placement. Our mission is to provide useful employment information to students to help them achieve their dreams. Senior students register detailed reports of their job hunting experiences, offering valuable insights to their juniors. By accessing this information, junior students can efficiently obtain job search information tailored to their interests and aptitudes.
Our research utilizes advanced machine learning technologies such as data mining and collaborative filtering. This allows us to develop practical systems directly connected to real-world job hunting. Through sharing experiences, seniors support the growth of juniors, fostering a strong community. We welcome passionate and collaborative students eager to learn and grow with us. Acquiring practical skills here will be a significant advantage in building your career. Join us in learning and paving the way for your future career.
Research
Research Theme 1
UI Optimization for Mobile Job Support Systems to Enhance UX
This research aims to optimize the user interface (UI) of mobile job support systems for students and improve user experience (UX) based on feedback from last year.
First, we will enhance the feedback messages during registration and login, and clarify labels on the user information update page. Next, we will fix issues such as malfunctioning mobile menu buttons and display problems during advice viewing, and introduce responsive design. Furthermore, we will expand the advanced search function and display the number of search results. Finally, we will review text color adjustments and default settings of forms, and add new features such as favorites.
These improvements are expected to enhance system usability and usage rates.
Research Theme 2
Introduction and Evaluation of Job Activity Recommendation Systems
This research aims to introduce and evaluate a recommendation system that efficiently accesses job activity reports matching students' interests and aptitudes. Current systems face challenges where students spend considerable time finding suitable reports.
We implement collaborative filtering algorithms to recommend highly relevant reports based on students' browsing and search histories. Specifically, we select and implement collaborative filtering algorithms, and introduce a related item recommendation feature. This enhances user engagement and increases site navigation rates.
The system's evaluation will be based on user engagement, revisit rates, usage rates, and registration rates, evaluating accuracy and effectiveness through feedback. Ultimately, we expect students to efficiently find more useful reports, thereby enhancing the quality of job activities.
Activities
Presentation of Research Achievements
On March 17, 2024, at the Database Applications Session of the 86th National Conference of the Information Processing Society of Japan held at Kanagawa University, Yokohama Campus, Mr. Mahbub from our laboratory presented the results of his graduation research as a representative of the laboratory. Mr. Mahbub presented on "Research on UX of Job Search Support Systems", and received two questions and advice from experts at the venue, making it a valuable experience before joining Fujitsu Limited.
Introduction to Research
During the 2023 campus festival, students at our laboratory booth introduced visitors to our research activities.
Video
Profile
CHIE ITO
Associate Professor at Daiichi Institute of Technology, Ueno Campus
Master of Engineering from the Graduate School of Electrical Communication, The University of Electro-Communications
Current Educational and Research Activities
- In charge of Java Programming I/II, Java Programming Exercises I/II, Object-Oriented Programming
- Engaged in research related to Web Systems and Databases
- Regular Member of the Information Processing Society of Japan
- Regular Member of the Database Society of Japan
- Regular Member of the Institute of Electronics, Information and Communication Engineers
- Regular Member of the Japanese Society for Artificial Intelligence
Past Educational Research and Technical Achievements
- Worked in systems development for approximately 10 years at OKI Software Co., Ltd.
Qualifications
- Fundamental Information Technology Engineer
- ORACLE MASTER Bronze Database 10g
Contact
Daiichi Insitute of Technology, Tokyo Ueno Campus, Faculty of Engineering
Department of Information, AI, and Data Science, Ito Laboratory
3rd Building, 1-7-4 Kitaueno, Taito-ku, Tokyo
E-mail：c.ito@ueno.daiichi-koudai.ac.jp
Website: https://ueno.daiichi-koudai.ac.jp/