Paper: Getting More from Segmentation Evaluation

ACL ID N12-1038
Title Getting More from Segmentation Evaluation
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2012
Authors

We introduce a new segmentation evaluation measure, WinPR, which resolves some of the limitations of WindowDiff. WinPR distin- guishes between false positive and false nega- tive errors; produces more intuitive measures, such as precision, recall, and F-measure; is in- sensitive to window size, which allows us to customize near miss sensitivity; and is based on counting errors not windows, but still pro- vides partial reward for near misses.