Lifestyle Segmentation Based on Contents of Uploaded Images Versus Ratings of Items
Clustering algorithms are standard tools for marketing purposes. So, e.g., 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 which reflect their activities, interests, and opinions. To compare whether contents of uploaded images lead to similar lifestyle segmentations as ratings of items, a comparison study was conducted among 478 people. In this paper we discuss the results of this study that suggests that similar lifestyle segmentations can be found. We discuss advantages and disadvantages of the new approach to lifestyle segmentation.
KeywordsHierarchical Cluster Analysis Feature Extraction Method Content Base Image Retrieval Enduring Belief Lifestyle Statement
This research is funded by Federal Ministry for Education and Research under grants 03FO3072. The author is responsible for the content of this paper.
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