Research > Faculty Projects

ExpertiseNet: Relational and Evolutionary User Modeling

Principal Investigator
Ming-Ting Sun

Sponsor(s)
NEC

Award Period
09/01/2004 - 12/30/2019

Abstract
It is important for enterprises to understand and manage the expertise of their employees. However, currently employee profiles are usually manually edited and updated, which is tedious work and often produces results of poor quality. To overcome this problem, we develop a user- centric modeling technology which dynamically describes and updates an employee's expertise. The technology can enhance employees' collaboration and productivity by finding people with complementary expertise, or people with expertise needed for a specific project. Instead of only using keywords as most traditional approaches do, we propose an evolutionary graph model which we call ExpertiseNet to describe the person. The temporal evolution and relational information of the expertise are explicitly described in ExpertiseNet; thus it is useful for mining, retrieval, and visualization.

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