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Study 4 - Mining ideas from textual information

 
: Thorleuchter, D.; Poel, D. van den; Prinzie, A.

:
Fulltext urn:nbn:de:0011-n-1678222 (291 KByte PDF)
MD5 Fingerprint: 7031f71802f621840834bae3964008ed
Created on: 1.7.2011


Thorleuchter, D. ; Poel, D. van den; Prinzie, A.:
Essays on text mining for improved decision making : Thesis contains seven Fraunhofer INT studies
Zelzate, Belgien: University press, 2011
pp.83-102
English
Book Article, Electronic Publication
Fraunhofer INT ()
idea mining; text mining; text classification; technology

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.

: http://publica.fraunhofer.de/documents/N-167822.html