Big data, little decisions: Tightening the loop between data crunching and human expertise | IEEE Conference Publication | IEEE Xplore

Big data, little decisions: Tightening the loop between data crunching and human expertise


Abstract:

This presentation is a case study examining how LexisNexis uses scaled active learning on the HPCC Systems environment to focus manual topical annotations on critical doc...Show More

Abstract:

This presentation is a case study examining how LexisNexis uses scaled active learning on the HPCC Systems environment to focus manual topical annotations on critical documents pulled from a large corpus. The active learning system uses natural language processing and machine learning techniques to identify and present “next best” training set candidates to legal editors, combining massive parallel processing with expert human analysis to improve classifier accuracy while minimizing human effort.
Date of Conference: 20-24 May 2013
Date Added to IEEE Xplore: 25 July 2013
ISBN Information:
Conference Location: San Diego, CA, USA

References

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