User-generated content for image clustering and marketing purposes

Abstract

The analysis of images for different purposes - particularly image clustering - has been the subject of several research streams in the past. Since the 1990s query by image content and, somewhat later, content-based image retrieval have been topics of growing scientific interest. A literature review shows that research on image analysis, so far, is primarily related to computer science. However, since the advent of Flickr and other media-sharing platforms there is an ever growing data base of images which reflects individual preferences regarding activities or interests. Hence, these data is promising to observe implicit preferences and complement classical efforts for several marketing purposes (see, e.g., Van House, Int J Hum-Comput Stud 67:1073-1086, 2009 or Baier D, Daniel I (2011) Image clustering for marketing purposes. In:W. Gaul, A. Geyer-Schulz, L. Schmidt- Thieme (eds) Challenges concerning the data analysis - Computer science - Optimization, vol. 43). Against this background, the present paper investigates options for clustering images on the basis of personal image preferences, e.g. to use the results for marketing purposes. © Springer International Publishing Switzerland 2013.