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Image Clustering for Marketing Purposes

  • Daniel BaierEmail author
  • Ines Daniel
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

Clustering algorithms are standard tools for marketing purposes. For example, in market segmentation, they are applied to derive homogeneous customer groups. However, recently, the available resources for this purpose have extended. So, e.g., in social networks potential customers provide images – and other information as e.g. profiles, contact lists, music or videos – which reflect their activities, interests, and opinions. Also, consumers are getting more and more accustomed to select or upload personal images during an online dialogue. In this paper we discuss, how the application of clustering algorithms to such uploaded image collections can be used for deriving market segments. Software prototypes are discussed and applied.

Keywords

Image Retrieval Color Histogram Market Segmentation Zernike Moment Image Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. ARD/ZDF (2010) ARD/ZDF-Onlinestudie 2010. www.ard-zdf-onlinestudie.de
  2. Baier D (2003) Classification and marketing research. Taksonomia 10:21–39Google Scholar
  3. Baier D, Brusch M (2008) Marktsegmentierung. In: Herrmann A, Homburg C, Klarmann M (eds) Handbuch Marktforschung, Methoden - Anwendungen - Praxisbeispiele. Gabler, Wiesbaden, pp 769–790Google Scholar
  4. Chen Y, Wang JZ, Krovetz R (2003) Content-based image retrieval by clustering. In: Proceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval (MIR 2003), Berkeley, CA, USA, pp 193–200Google Scholar
  5. Choras RS (2007) Image feature extraction techniques and their applications for CBIR and biometrics systems. Int J Biol Biomed Eng 1(1):6–16Google Scholar
  6. Datta R, Joshi D, Li J, Wang JZ (2008) Image retrieval: Ideas, influences, and trends of the new age. ACM Comput Surv 40(2):5:1–5:60Google Scholar
  7. Gaul W, Baier D (1994) Marktforschung und Marketing Management: Computerbasierte Entscheidungsunterstützung. Oldenbourg, MünchenGoogle Scholar
  8. van House N (2007) Flickr and public image-sharing: Distant closeness and photo exhibition. In: Conference on Human Factors in Computing Systems, San Jose, CA, USA, pp 2717–2722Google Scholar
  9. Law M, Figueiredo M, Jain AK (2004) Simultaneous feature selection and clustering using mixture model. IEEE Trans Pattern Anal Mach Intell 26(9):1154–1166CrossRefGoogle Scholar
  10. Lew MS, Sebe N, Djeraba C, Jainl R (2006) Content-based multimedia information retrieval: State of the art and challenges. ACM Trans Multimedia Comput Comm Appl 2(1):1–19CrossRefGoogle Scholar
  11. Maheshwari M, Silakari S, Motwani M (2009) Image clustering using color and texture. In: First International Conference on Computational Intelligence, Communication Systems and Networks, July 23–25, 2009, Indore, India, pp 403–408Google Scholar
  12. Rodden K, Basalej W, Sinclair D, Wood KR (2001) Does organisation by similarity assist image browsing? In: Proceedings of Human Factors in Computing Systems, March-31-April 5, 2001, Seattle, Washington, USA, pp 190–197Google Scholar
  13. Schmitt I (2005) Ähnlichkeitssuche in Multimedia-Datenbanken - Retrieval, Suchalgorithmen und Anfragebehandlung. Oldenbourg, MünchenGoogle Scholar
  14. Sinus Sociovision (2009) Informationen zu den Sinus-Milieus 2009. Sinus Sociovision GmbH, Heidelberg.Google Scholar
  15. Smith W (1956) Product differentiation and market segmentation as alternative marketing strategies. J Market 21:3–8CrossRefGoogle Scholar
  16. Wedel M, Kamakura WA (2000) Market segmentation: conceptual and methodological foundations. Kluwer, DordrechtGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Institute of Business Administration and EconomicsBrandenburg University of Technology CottbusCottbusGermany

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