Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1698189 | Procedia CIRP | 2016 | 6 Pages |
Abstract
Along the product life-cycle, industrial processes generate massive digital assets containing precious information. Besides structured databases, written reports hold unstructured information hardly exploitable due to the lack of vocabulary and syntax standardization. In this paper we present a methodology and natural language processing approach to exploit these documents. Our method consists in providing connections based on supervised retrieval of domain-specific expressions. No prior document analysis are required to drive the algorithm. It underlines a scale of specificity in pattern visualization. This allows relevant and specific information extraction for feedback (e.g. design stage, after-sales service).
Related Topics
Physical Sciences and Engineering
Engineering
Industrial and Manufacturing Engineering
Authors
Matthieu Quantin, Benjamin Hervy, Florent Laroche, Alain Bernard,