E-COMMERCE RECOMMENDATION SYSTEM AND METHOD

摘要

Disclosed herein is item recommender that uses a model trained using a combination of at least visual item similarity training data and social activity training data. The model may be used, for example, to identify a set of recommended products having similar visual features as a given product. The set of recommended products may be presented to the user along with the given product. The model may be continuously updated using feedback from users to identify the features considered to be important to the users relative to other features.

主权项

1. A method comprising:
determining, by at least one computing device, visual similarity training data for a plurality of items, the visual similarity training data identifying, for each pair of items of the plurality of items, a level of visual similarity between images of the items in the pair; determining, by the at least one computing device, social activity training data for the plurality of items, the social activity training data identifying, for each pair of items of the plurality of items, an indicator of whether a shared user interest in the pair of items exists; training, by the at least one computing device, a model using a training data comprising the image similarity training data and the social activity training data; and generating, by the at least one computing device, a set of recommended items using the trained model.