Overview
Topic status: We're looking for students to study this topic.
Project summary
As information overload problem has been a serious issue for Web users, how to help users deal with this problem becomes very important. Recently, personalised recommender systems have been developed to overcome the information overload problem and provide personalised content, services and information items to potential consumers.
The goal of this project is to develop a recommender system for recommending scientific articles based on the data collected in QUT ePrints site. The recommender system includes these components to be developed in this project:
- user profiling component to generate users' interests based on server log data
- recommendation model including design and implementation of recommendation algorithms
- database construction
- a graphic user interface (GUI) to communicate with users to:
- get users' queries or requests and also provide recommendations
- navigate topic hierarchy to find the topics of users' interest.
Required student skills/experience
IT, science, or engineering background, with knowledge in software development and databases.
- Study level
- Vacation research experience scholarship
- Supervisors
- QUT
- Organisational unit
Science and Engineering Faculty
- Research area
- Keywords
- recommender systems, scientific articles
- Contact
-
Please contact the supervisor.
Associate Professor Yue Xu
