Computational Statistics & Data Analysis - Nonlinear methods and data mining
Implementing the "GrabCut" segmentation technique as a plugin for the GIMP
AFRIGRAPH '06 Proceedings of the 4th international conference on Computer graphics, virtual reality, visualisation and interaction in Africa
The impact of images on user clicks in product search
Proceedings of the Twelfth International Workshop on Multimedia Data Mining
Is a picture really worth a thousand words?: - on the role of images in e-commerce
Proceedings of the 7th ACM international conference on Web search and data mining
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In this paper we study the importance of image based features on the click-through rate (CTR) in the context of a large scale product search engine. Typically product search engines use text based features in their ranking function. We present a novel idea of using image based features, common in the photography literature, in addition to text based features. We used a stochastic gradient boosting based regression model to learn relationships between features and CTR. Our results indicate statistically significant correlations between the image features and CTR. We also see improvements to NDCG and mean standard regression.