ASQ

Exclusive Content & Downloads from ASQ

Mining and Tracking Massive Text Data

Summary: A comprehensive data-mining procedure is proposed for examining large freestyle text datasets to identify useful features and develop appropriate tracking statistics. Specific text analysis methodologies and tracking statistics are discussed, and several approaches for incorporating misclassified data or error measurements into the inference for tracking statistics are proposed and evaluated. The proposed procedure is demonstrated in the analysis of an aviation safety report repository to show its usefulness in aviation risk management and general decision-support.

Anyone with a subscription, including Site and Enterprise members, can access this article.


Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

  • Topics: Data Quality, Standards
  • Keywords: Data retrieval, Missing data, Risk analysis, Data analysis, Text classification, Tracking system
  • Author: Jeske, Daniel R.; Liu, Regina Y.
  • Journal: Technometrics