Finding New Technological Ideas and Inventions with Text Mining and Technique Philosophy

  • Dirk Thorleuchter
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


Text mining refers generally to the process of deriving high quality information from unstructured texts. Unstructured texts come in many shapes and sizes. It may be stored in research papers, articles in technical periodicals, reports, documents, web pages etc. Here we introduce a new approach for finding textual patterns representing new technological ideas and inventions in unstructured technological texts.

This text mining approach follows the statements of technique philosophy. Therefore a technological idea or invention represents not only a new mean, but a new purpose and mean combination. By systematic identification of the purposes, means and purpose-mean combinations in unstructured technological texts compared to specialized reference collections, a (semi-) automatic finding of ideas and inventions can be realized. Characteristics that are used to measure the quality of these patterns found in technological texts are comprehensibility and novelty to humans and usefulness for an application.


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  1. FELDMAN, R. and DAGAN, I. (1995): Kdt - knowledge discovery in texts. In: Proceedings of the First International Conference on Knowledge Discovery (KDD). Montreal, 112-113.Google Scholar
  2. FENNER, J. and THORLEUCHTER, D. (2006): Strukturen und Themengebiete der mittel- standsorientierten Forschungsprogramme in den USA. Fraunhofer INT’s edition, Euskirchen, 2.Google Scholar
  3. HOTHO, A. (2004): Clustern mit Hintergrundwissen. Univ. Diss., Karlsruhe, 29.zbMATHGoogle Scholar
  4. IPSEN, C. (2002): F&E-Programmplanung bei variabler Entwicklungsdauer. Verlag Dr. Ko-vac, Hamburg, 10.Google Scholar
  5. KAMPHUSMANN, T. (2002): Text-Mining. Symposion Publishing, Düsseldorf, 28.Google Scholar
  6. LUSTIG, G. (1986): Automatische Indexierung zwischen Forschung und Anwendung. Georg Olms Verlag, Hildesheim, 92.Google Scholar
  7. RIPKE, M. and STÖBER, G. (1972): Probleme und Methoden der Identifizierung potentieller Objekte der Forschungsförderung. In: H. Paschen and H. Krauch (Eds.): Methoden und Probleme der Forschungs- und Entwicklungsplanung. Oldenbourg, München, 47.Google Scholar
  8. ROHPOHL, G. (1996): Das Ende der Natur. In: L. Schäfer and E. Sträker (Eds.): Naturauf-fassungen in Philosophie, Wissenschaft und Technik. Bd. 4, Freiburg, München, 151.Google Scholar
  9. STRUBE, G. (2003): Menschliche Informationsverarbeitung. In: G. Görz, C.-R. Rollinger and J. Schneeberger (Eds.): Handbuch der Künstlichen Intelligenz. 4. Auflage, Oldenbourg, München, 23-28.Google Scholar
  10. THORLEUCHTER, D. (2007): Überblick über F&T-Vorhaben und ihre Ansprechpartner im Bereich BMVg. Fraunhofer Publica, Euskirchen, 2-88.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Dirk Thorleuchter
    • 1
  1. 1.Fraunhofer INTEuskirchenGermany

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