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Mining Ideas from Textual Information

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Author Info

  • D. THORLEUCHTER
  • D. VAN DEN POEL

    ()

  • A. PRINZIE
  • -

Abstract

This approach introduces idea mining as process of extracting new and useful ideas from unstructured text. We use an idea definition from technique philosophy and we focus on ideas that can be used to solve technological problems. The rationale for the idea mining approach is taken over from psychology and cognitive science and follows how persons create ideas. To realize the processing, we use methods from text mining and text classification (tokenization, term filtering methods, Euclidean distance measure etc.) and combine them with a new heuristic measure for mining ideas. As a result, the idea mining approach extracts automatically new and useful ideas from a user given text. We present these problem solution ideas in a comprehensible way to support users in problem solving. This approach is evaluated with patent data and it is realized as a web-based application, named 'Technological Idea Miner' that can be used for further testing and evaluation.

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File URL: http://www.feb.ugent.be/nl/Ondz/wp/Papers/wp_09_619.pdf
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Bibliographic Info

Paper provided by Ghent University, Faculty of Economics and Business Administration in its series Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium with number 09/619.

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Length: 16 pages
Date of creation: Nov 2009
Date of revision:
Handle: RePEc:rug:rugwps:09/619

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Related research

Keywords: Idea Mining; Text Mining; Text Classification; Technology;

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Cited by:
  1. D. Thorleuchter & D. Van Den Poel & A. Prinzie, 2011. "Analyzing existing customers’ websites to improve the customer acquisition process as well as the profitability prediction in B-to-B marketing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 11/733, Ghent University, Faculty of Economics and Business Administration.
  2. D. Thorleuchter & D. Van Den Poel, 2012. "Improved Multilevel Security with Latent Semantic Indexing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/811, Ghent University, Faculty of Economics and Business Administration.
  3. D. Thorleuchter & D. Van Den Poel, 2012. "Protecting Research and Technology from Espionage," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/824, Ghent University, Faculty of Economics and Business Administration.
  4. D. Thorleuchter & D. Van Den Poel, 2012. "Technology Classification with Latent Semantic Indexing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 12/814, Ghent University, Faculty of Economics and Business Administration.
  5. D. Thorleuchter & D. Van Den Poel, 2013. "Weak Signal Identification with Semantic Web Mining," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/860, Ghent University, Faculty of Economics and Business Administration.

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