Image placement order optimization for mobile commerce

With the increase in popularity of mobile commerce, the placement order of images on mobile displays is an important factor to attract and retain customers' attention. In this paper, we propose a novel method to optimize the placement of item images based upon the relative attractiveness of each image to the customer. To judge this, the proposed method estimates the leave rate of the customer at each image for each ordering using a model based on unsupervised hierarchical clustering. This allows estimating the expected leave rate for different image placements, solving an optimization problem to obtain the best ordering. The model is evaluated using a dataset collected from Rakuten Ichiba, the largest e-commerce site in Japan.

[1]  Jürgen Schmidhuber,et al.  Long Short-Term Memory , 1997, Neural Computation.

[2]  Fei-Fei Li,et al.  ImageNet: A large-scale hierarchical image database , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.

[3]  Bruce E. Sagan,et al.  The symmetric group - representations, combinatorial algorithms, and symmetric functions , 2001, Wadsworth & Brooks / Cole mathematics series.

[4]  H. Hotelling Analysis of a complex of statistical variables into principal components. , 1933 .

[5]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[6]  Robert Tibshirani,et al.  Estimating the number of clusters in a data set via the gap statistic , 2000 .

[7]  Avinash C. Kak,et al.  PCA versus LDA , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Fraser,et al.  Independent coordinates for strange attractors from mutual information. , 1986, Physical review. A, General physics.

[9]  Lukás Burget,et al.  Recurrent neural network based language model , 2010, INTERSPEECH.