User-Generated Content for Image Clustering and Marketing Purposes

Schindler D. User-Generated Content for Image Clustering and Marketing Purposes. In: Lausen B, Van den Poel D, Ultsch A, eds. Algorithms from and for Nature and Life, Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Cham u.a.: Springer; 2013: 473-480.The analysis of images for different purposes – particularly image clustering – has been the subject of several research streams in the past. Since the 90s 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 are promising to observe implicit preferences and complement classical efforts for several marketing purposes (see, e.g., van House 2009 or Baier and Daniel 2011). Against this background, the present paper investigates options for clustering images on the basis of personal image preferences, e.g. to use results for marketing purposes