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Mining ideas from textual information

 
: Thorleuchter, D.

Gesellschaft für Klassifikation; International Federation of Classification Societies -IFCS-; British Classification Society -BCS-; Dutch/Flemish Classification Society -VOC-:
32nd Annual Conference Advances in Data Analysis, Data Handling and Business Intelligence 2008 : Joint conference with the Britisch Classification Society (BCS) and the Dutch/Flemish Classification Society (VOC), July 16-18, 2008, Hamburg
Hamburg, 2008
S.147
Gesellschaft für Klassifikation (GfKl Annual Conference) <32, 2008, Hamburg>
Englisch
Konferenzbeitrag
Fraunhofer INT ()
textmining; knowledge; discovery; idea

Abstract
This paper describes an approach to find automatically new technological ideas in textual information. On the basis of (Thorleuchter (2008)) the existing theoretical algorithm is enlarged in consideration of text mining approaches like stemming, term frequency etc. (Ferber (2003)) and "creativity technique" approaches from literature (Dean et al. (2001)). The aim of the new algorithm is to find ideas by using a general stop word list, because up to now the existing approach is based on the inefficient usage of a (domain) specific stop word list specific created for the analyzed text. This new approach is evaluated with non-proprietary data and it is realized as web-based application, named "Technological Idea Miner" that can be used for further testing and evaluation. The presentation of the identified ideas will be displayed in consideration of cognitive research knowledge like described in (Puppe et al. (2003)).

: http://publica.fraunhofer.de/dokumente/N-113509.html