CHISSL: A Human-Machine Collaboration Space for Unsupervised Learning

Conference · Fri Jul 14 00:00:00 EDT 2017

DOI:https://doi.org/10.1007/978-3-319-58628-1_33· OSTI ID:1373854

Arendt, Dustin L.; Komurlu, Caner; Blaha, Leslie M.

We developed CHISSL, a human-machine interface that utilizes supervised machine learning in an unsupervised context 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.

• Research Organization: Pacific Northwest National Laboratory (PNNL), Richland, WA (US)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1373854
• Report Number(s): PNNL-SA-124302
• Country of Publication: United States
• Language: English

Related Subjects

Active Learning
Human-machine Interface
Interactive Clustering
Semi-supervised Learning
direct manipulation