Information recommendation method based on deep learning

The invention discloses an information recommendation method based on deep learning. The method comprises the following steps: S1, inputting a data set into a recommendation system; and S2, in the recommendation system, performing data processing on the data set in a recall stage, a sorting stage and a feature processing stage of the deep learning model in sequence to obtain an information recommendation result. An improved probability matrix decomposition model is provided, personal interests, preferences and the like of consumers or commodities are integrated, and purposiveness and accuracy of RS recall can be improved; meanwhile, an FWHFM model based on the deep neural network is constructed, an FHWFM interaction layer generated by a feature domain pair embedding matrix and a feature embedding vector is spliced with an original feature vector layer, training is carried out through the deep neural network DNN, and the click rate estimation effect is obviously superior to that of other deep models; and based on the improvement of the two models in the recommendation system, the accuracy of information recommendation in the information recommendation process is improved.