E-commerce recommendation system and method
AssigneeYahoo! Inc.
InventorsJen-Hao Hsiao, Nan Liu, Jia Li
Life of this patent
Estimating the term…
Abstract
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.
Claims21
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.
A system comprising:
- at least one computing device, each computing device comprising a processor and a storage medium for tangibly storing thereon program logic for execution by the processor, the stored program logic comprising:
- first determining logic for determining 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;
- second determining logic for determining 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 logic for training a model using a training data comprising the image similarity training data and the social activity training data;
- and
- generating logic for generating, using the trained model, a set of recommended items.
A computer readable non-transitory storage medium for tangibly storing thereon computer readable instructions that when executed cause at least one processor to:
- determine 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;
- determine 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;
- train a model using a training data comprising the image similarity training data and the social activity training data;
- and
- generate a set of recommended items using the trained model.
Dependencies are inferred from the claim text.