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PRIME: A Personalized Recommendation for Information VIsualization Methods via Extended matrix Completion

詳細技術說明

Information visualization is an important mode of human-computer interaction to acquire insights of complex datasets. However, a uniform visualization format may be inefficient to bring the insights to different users at different contexts due to the users' differences in knowledge, perception, and cognition capabilities. On the other hand, typical visualization evaluation methods were conducted in an offline manner hence reducing the efficiency. Thus, a real-time and personalized visualization recommendation approach is needed. This intellectual property provides a real-time visualization recommendation methodology to select the best designs for different users at different contexts (i.e., tasks) by extracting user mental and physical profiles from wearable sensing devices and user input behaviors.

*Abstract

None

*Principal Investigation

Name: Ran Jin, Assistant Professor

Department: Industrial and Systems Engineering

Name: Xiaoyu Chen, Ph.D. Student

Department: Industrial and Systems Engineering

Name: Nathan Lau, Assistant Professor

Department: Industrial & Systems Engineering

國家/地區

美國