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AAAI
2011

Effective End-User Interaction with Machine Learning

12 years 3 months ago
Effective End-User Interaction with Machine Learning
End-user interactive machine learning is a promising tool for enhancing human productivity and capabilities with large unstructured data sets. Recent work has shown that we can create end-user interactive machine learning systems for specific applications. However, we still lack a generalized understanding of how to design effective end-user interaction with interactive machine learning systems. This work presents three explorations in designing for effective end-user interaction with machine learning in CueFlik, a system developed to support Web image search. These explorations demonstrate that interactions designed to balance the needs of end-users and machine learning algorithms can significantly improve the effectiveness of end-user interactive machine learning.
Saleema Amershi, James Fogarty, Ashish Kapoor, Des
Added 12 Dec 2011
Updated 12 Dec 2011
Type Journal
Year 2011
Where AAAI
Authors Saleema Amershi, James Fogarty, Ashish Kapoor, Desney S. Tan
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