.png){kind=icon}
.png){kind=icon}
Return
Automatic case acquisition from texts for process-oriented case-based reasoning
.png){kind=icon}
OA
AI
DOI：10.1016/j.is.2012.11.014.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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. (C) 2012 Elsevier Ltd. All rights reserved.
Keywords:
Automatic case acquisition
Information extraction
Natural language processing
Process-oriented case-based reasoning
Textual case-based reasoning
Workflow generation
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.9
Papers:
2.8K
Citations:
1.8K