Title :
Clustering the open ended future needs
Author :
Çinar, Didem ; Kayakutlu, Gülgün
Author_Institution :
Ind. Eng. Dept, Istanbul Tech. Univ., Istanbul, Turkey
Abstract :
This paper aims to propose a solution for clustering the trends in vague conditions by comparing the results of hard c-means and fuzzy c-means algorithms. Application is done on an SME survey indicating the future needs for the improvements in regional innovation. Application results indicate that fuzzy c-means clustering algorithm gives significantly achievable results that guide innovation experts in their regional development perspective.
Keywords :
fuzzy set theory; innovation management; pattern clustering; small-to-medium enterprises; SME survey; fuzzy c-mean clustering algorithm; hard c-mean algorithm; regional development perspective; regional innovation expert; small-to-medium company; Clustering algorithms; Collaboration; Collaborative work; Companies; Economics; Industrial engineering; Local government; Productivity; Research and development; Technological innovation;
Conference_Titel :
Management of Engineering & Technology, 2009. PICMET 2009. Portland International Conference on
Conference_Location :
Portland, OR
Print_ISBN :
978-1-890843-20-5
Electronic_ISBN :
978-1-890843-20-5
DOI :
10.1109/PICMET.2009.5262067
