Abstract: A computer-implemented method includes generating a first list of products to recommend to a user. The following steps are then repeated: removing a first product from the first list and placing the first product in a second list wherein the order of the products in the second list determines the order that products appear on a user interface; and comparing each remaining product in the first list to the product placed on the second list and moving products that are similar to the product placed on the second list further down in the first list. A user interface is then generated from the second list to show suggested products to a user.

Abstract: A computer-implemented method includes accessing web page content for a product, the web page content comprising text tokens for at least two different fields of a web page that is displayed to convey information about the product. Respective weights of each field of the web page are retrieved and are used with the text tokens of each field to generate a product vector, where each unique text token provides a dimension of the product vector and the weights are used to provide a weight for each dimension. The product vector is used to identify products to recommend to a user and a user interface is displayed showing the identified products.

Abstract: A computer-implemented method includes determining a similarity score for a product by determining a similarity between a product vector for a product and a user vector for a user, determining a recency score for the product based on a date the product was made available at a retailer, and determining collaborative filtering score for the product based on the likelihood that people who bought another product would also buy the product. The similarity score, the recency score and the collaborative filtering score are combined to generate a total score for the product. Based on the total score for the product, a user interface is generated to recommend the product to the user.

Abstract: A computer-implemented method includes generating a first list of products to recommend to a user. The following steps are then repeated: removing a first product from the first list and placing the first product in a second list wherein the order of the products in the second list determines the order that products appear on a user interface; and comparing each remaining product in the first list to the product placed on the second list and moving products that are similar to the product placed on the second list further down in the first list. A user interface is then generated from the second list to show suggested products to a user.