Interactive image recommendation system.
Bo Qirong, Jinye Peng, Daxiang Li · Computer Engineering and Applications Journal · 2011
With the rapid development of Internet technology,image documents have become an important information source. It is hard to retrieve certain images from all available ones.This paper proposes an interactive image recommendation system, which uses color histogram feature or Gabor texture feature to express image contents,then a kernel based K-meanse is utilized to cluster images into multiple classes by their visual features,finally based on a sample and hyperbolic techniques,images are recommended and displayed.The experimental results demonstrate that the proposed system can recommend and display the similar images from the same class efficiently,when users click on the images they are interested in.