Computer-aided analysis of patents and search for TRIZ contradictions

Gaetano Cascini and Davide Russo

International Journal of Product Development, 2007, vol. 4, issue 1/2, 52-67

Abstract: TRIZ, the Soviet-initiated Theory of Inventive Problem Solving, is gaining acknowledgement both as a systematic methodology for innovation and a powerful tool for technology forecasting. Nevertheless, the analysis of patents necessary for gathering the data to be used for the previsional activity is very cumbersome and sometimes unworthy due to the intrinsic low reliability of forecasting tasks. With this perspective it is necessary to speed up the identification of the technical/physical conflict(s) overcome by an invention, according to its textual description. Although text-mining tools have reached relevant capabilities for extracting useful information from huge sets of documents, no specific means are available to support the analysis of patents with the aim of identifying the contradiction underlying a given technical system. This paper proposes a computer-aided approach for accomplishing such a task: the algorithm is described and validated by means of practical examples.

Keywords: text mining; patents analysis; TRIZ; contradictions analysis; technology forecasting; product development; inventive problem solving; innovation; computer-aided analysis. (search for similar items in EconPapers)
Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.inderscience.com/link.php?id=11533 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpdev:v:4:y:2007:i:1/2:p:52-67

Access Statistics for this article

More articles in International Journal of Product Development from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().