Mining ideas from textual information

Authors:
Dirk Thorleuchter;Dirk Van den Poel;Anita Prinzie
Affiliations:
Fraunhofer INT, D-53879 Euskirchen, Appelsgarten 2, Germany;Ghent University, B-9000 Gent, Tweekerkenstraat 2, Belgium;Ghent University, B-9000 Gent, Tweekerkenstraat 2, Belgium and Visiting Researcher, Manchester Business School, The University of Manchester, Manchester M15-6PB, Booth Street West, UK
Venue:
Expert Systems with Applications: An International Journal
Year:
2010

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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.