A Risk Assessment System with Automatic Extraction of Event Types

نویسندگان

  • Philippe Capet
  • Thomas Delavallade
  • Takuya Nakamura
  • Ágnes Sándor
  • Cedric Tarsitano
  • Stavroula Voyatzi
چکیده

In this article we describe the joint effort of experts in linguistics, information extraction and risk assessment to integrate EventSpotter, an automatic event extraction engine, into ADAC, an automated early warning system. By detecting as early as possible weak signals of emerging risks ADAC provides a dynamic synthetic picture of situations involving risk. The ADAC system calculates risk on the basis of fuzzy logic rules operated on a template graph whose leaves are event types. EventSpotter is based on a general purpose natural language dependency parser, XIP, enhanced with domain-specific lexical resources (LexiconGrammar). Its role is to automatically feed the leaves with input data.

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تاریخ انتشار 2008