Systems and methods for labeling source data using confidence labels
Creators
Abstract
Systems and methods for the annotation of source data using confidence labels in accordance embodiments of the invention are disclosed. In one embodiment of the invention, a method for determining confidence labels for crowdsourced annotations includes obtaining a set of source data, obtaining a set of training data representative of the set of source data, determining the ground truth for each piece of training data, obtaining a set of training data annotations including a confidence label, measuring annotator accuracy data for at least one piece of training data, and automatically generating a set of confidence labels for the set of unlabeled data based on the measured annotator accuracy data and the set of annotator labels used.
Additional Information
Application filed: May 27, 2016. Patent granted: July 11, 2017.Attached Files
Published - US9704106B2.pdf
Files
US9704106B2.pdf
Files
(1.6 MB)
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Additional details
Identifiers
- Eprint ID
- 87107
- Resolver ID
- CaltechAUTHORS:20180614-120834409
Related works
Dates
- Created
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2018-07-05Created from EPrint's datestamp field
- Updated
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2019-10-03Created from EPrint's last_modified field