Congress 1310
  • Yago Fontenla-Seco, Alberto Bugarín, Manuel Lama
  • 1st Foundations of Trustworthy AI - Integrating Learning, Optimization and Reasoning Workshop. Santiago de Compostela, España. 2020

Process-To-Text: a framework for the quantitative description of processes in natural language

In this paper we present the Process-To-Text (P2T) framework for the automatic generation of textual descriptive explanations of business processes in natural language. P2T integrates three AI paradigms: process mining for extracting temporal and structural information from a process, fuzzy linguistic protoforms for modelling uncertain terms and natural language generation for building the explanations. A real usecase in the medical domain is presented, showing the potential of P2T for providing natural language explanations addressed to cardiology specialists.
Keywords: Process mining, Natural Language Generation, AutoAI, Explainable AI
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