An interactive tool for supporting error analysis for text mining

Authors:
Elijah Mayfield;Carolyn Penstein-Rosé
Affiliations:
Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA
Venue:
HLT-DEMO '10 Proceedings of the NAACL HLT 2010 Demonstration Session
Year:
2010

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Abstract

This demo abstract presents an interactive tool for supporting error analysis for text mining, which is situated within the Summarization Integrated Development Environment (SIDE). This freely downloadable tool was designed based on repeated experience teaching text mining over a number of years, and has been successfully tested in that context as a tool for students to use in conjunction with machine learning projects.