We developed CHISSL, a human-machine interface that utilizes interactive supervision to help the user group unlabeled instances by her own mental model. The user primarily interacts via correction (moving a misplaced instance into its correct group) or confirmation (accepting that an instance is placed in its correct group). Concurrent with the user’s interactions, CHISSL trains a classification model guided by the user’s grouping of the data. It then predicts the group of unlabeled instances and arranges some of these alongside the instances manually organized by the user. We hypothesize that this mode of human and machine collaboration is more effective than Active Learning, wherein the machine decides for itself which instances should be labeled by the user. We found supporting evidence for this hypothesis in a pilot study where we applied CHISSL to organize a collection of handwritten digits.
CITATION STYLE
Arendt, D., Komurlu, C., & Blaha, L. M. (2017). CHISSL: A human-machine collaboration space for unsupervised learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10284 11th International Conference, AC 2017, Held as Part of HCI International 2017, Vancouver, BC, Canada, July 9-14, 2017, Proceedings, Part I, pp. 429–448). Springer Verlag. https://doi.org/10.1007/978-3-319-58628-1_33
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