Carnegie Mellon University
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Outlier Finding: Focusing User Attention on Possible Errors

journal contribution
posted on 2001-01-01, 00:00 authored by Robert Miller, Brad Myers

When users handle large amounts of data, errors are hard to notice. Outlier finding is a new way to reduce errors by directing the user's attention to inconsistent data which may indicate errors. We have implemented an outlier finder for text, which can detect both unusual matches and unusual mismatches to a text pattern. When integrated into the user interface of a PBD text editor and tested in a user study, outlier finding substantially reduced errors.

History

Date

2001-01-01