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Associate researcher

Supervisor of Master's Candidates

School/Department:School of Computer Science and Information Engineering

Administrative Position:Associate Professor

Education Level:Postgraduate (Postdoctoral)


Degree:Doctoral degree


Alma Mater:Macquarie University

Discipline:Other specialties in Software Engineering
Computer Software and Theory
Computer Applications Technology
Other specialties in Computer Science and Technology

Lei Li



Education Level:Postgraduate (Postdoctoral)

Alma Mater:Macquarie University

Research Focus

Current position: Homepage lilei /Research Focus
Preference Completion

Preference completion has been widely applied in multiple fields, such as social selection and recommendation systems. In these fields, each user only has a partial ranking for certain entities, and it is often unrealistic for users to provide a complete ranking for all entities. The goal of preference completion is to infer a complete preference ranking for all items for each individual based on their incomplete preference ranking. However, in many cases, users may give an unreasonable ranking or a noisy version of their preference ranking. Therefore, how to more accurately complete users' preferences in the presence of noise is a continuous research issue. On the other hand, data in preference completion problems often have multi-source, dynamic, and massive features, so how to improve the algorithm's time performance while ensuring accuracy is also a key issue.