Problem Description

نویسندگان

  • Alan Mandell
  • Dan Binney
  • Lila Ghemri
  • David Fisher
چکیده

MetLife processes over 300,000 life insurance applications a year. Underwriting of these applications is labor intensive. Automation is difficult since they include many freeform text fields. MITA, MetLife’s Intelligent Text Analyzer, uses the Information Extraction --IE-technique of Natural Language Processing to structure the extensive text fields on a life insurance application. Knowledge engineering, with the help of underwriters as domain experts, was performed to elicit significant concepts for both medical and occupational text fields. A corpus of 20,000 life insurance applications provided the syntactical and semantic patterns in which these underwriting concepts occur. The extracted information can then be analyzed by conventional knowledge based systems. We project that MlTA and knowledge based analyzers will increase underwriting productivity by 20 to 30%.

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تاریخ انتشار 1999