Transforming unstructured natural language descriptions into measurable process performance indicators using Hidden Markov Models
作者:
Highlights:
• We propose an approach to make natural language PPI descriptions measurable.
• The approach transforms unstructured descriptions into a structured notation.
• The fully automated approach builds on Hidden Markov Models to parse descriptions.
• Quantitative evaluation demonstrates the applicability of the approach in practice.
摘要
•We propose an approach to make natural language PPI descriptions measurable.•The approach transforms unstructured descriptions into a structured notation.•The fully automated approach builds on Hidden Markov Models to parse descriptions.•Quantitative evaluation demonstrates the applicability of the approach in practice.
论文关键词:Performance measurement,Process Performance Indicators,Natural language processing,Hidden Markov Models,Model alignment
论文评审过程:Received 2 September 2016, Revised 29 May 2017, Accepted 26 June 2017, Available online 27 June 2017, Version of Record 3 July 2017.
论文官网地址:https://doi.org/10.1016/j.is.2017.06.005