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Overview based example selection in end user interactive concept learning
2009
Proceedings of the 22nd annual ACM symposium on User interface software and technology - UIST '09
Interaction with large unstructured datasets is difficult because existing approaches, such as keyword search, are not always suited to describing concepts corresponding to the distinctions people want to make within datasets. One possible solution is to allow end-users to train machine learning systems to identify desired concepts, a strategy known as interactive concept learning. A fundamental challenge is to design systems that preserve end-user flexibility and control while also guiding
doi:10.1145/1622176.1622222
dblp:conf/uist/AmershiFKT09
fatcat:4jyp4yk4irboxpkpy6jnjg7qzi