Automatic case acquisition from texts for process-oriented case-based reasoning

TL;DR

This paper presents a method for automatically extracting rich, process-oriented cases from free text, particularly assembly instructions, using natural language processing techniques to facilitate process reasoning in case-based systems.

Contribution

It introduces a novel methodology for automatic case acquisition from procedural texts, extending NLP techniques to process-oriented case representations for reasoning tasks.

Findings

Successful extraction of workflows from recipe texts

NLP techniques provide satisfactory results for case acquisition

Automated approach reduces manual effort in case engineering

Abstract

This paper introduces a method for the automatic acquisition of a rich case representation from free text for process-oriented case-based reasoning. Case engineering is among the most complicated and costly tasks in implementing a case-based reasoning system. This is especially so for process-oriented case-based reasoning, where more expressive case representations are generally used and, in our opinion, actually required for satisfactory case adaptation. In this context, the ability to acquire cases automatically from procedural texts is a major step forward in order to reason on processes. We therefore detail a methodology that makes case acquisition from processes described as free text possible, with special attention given to assembly instruction texts. This methodology extends the techniques we used to extract actions from cooking recipes. We argue that techniques taken from natural language processing are required for this task, and that they give satisfactory results. An evaluation based on our implemented prototype extracting workflows from recipe texts is provided.