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2010
Journal Article
Title

Mining ideas from textual information

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 an 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.
Author(s)
Thorleuchter, Dirk  
Fraunhofer-Institut für Naturwissenschaftlich-Technische Trendanalysen INT  
Poel, D. van den
Ghent University, Faculty of Economics and Business Administration
Prinzie, A.
Ghent University, Faculty of Economics and Business Administration
Journal
Expert Systems with Applications  
File(s)
Download (349.48 KB)
DOI
10.1016/j.eswa.2010.04.013
10.24406/publica-r-222727
Additional link
Full text
Language
English
Fraunhofer-Institut für Naturwissenschaftlich-Technische Trendanalysen INT  
Keyword(s)
  • idea mining

  • text mining

  • text classification

  • technology

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