Recommendation method and device based on deep learning

The invention discloses a recommendation method based on deep learning, and the method comprises the steps: obtaining a plurality of user portraits and a plurality of commodity attributes, and locking a target user according to the plurality of user portraits; extracting the explicit features of the target user and the explicit features of the multiple commodity attributes and then processing the explicit features to generate a recommendation list; learning the hidden features of the target user and the hidden features of the plurality of commodity attributes by using a deep learning model, and predicting the score of the target user on the recommendation list according to the hidden features; pre-recommending the commodities in the recommendation list to the target user, determining whether the target user receives recommendation, and if yes, recommending related information of the commodities according to the score of the recommendation list and the priority. According to the method and device, multi-dimens