Abstract: An image recommendation system extracts multiple sets of feature vectors from each of a plurality of images in an image catalog using multiple image classification algorithms. For a first image in the plurality of images, the recommendation system generates multiple similarity scores between the first image and each of one or more other images in the image catalog based on the feature vectors extracted from the first image and the one or more other images using each of the multiple image classification algorithms. A first set of weights is applied to the multiple similarity scores to generate respective weighted similarity scores between the first image and each of the one or more other images. The weighted similarity scores are stored, and used to select images that are similar to the first image.