2results about How to "Improve push accuracy" patented technology

This application discloses a data processing method, apparatus, computer-readable storage medium, and computer device, relating to the field of Internet technology. It involves acquiring user behavior data and obtaining item latent semantic vectors based on the user behavior data; performing clustering processing on the item latent semantic vectors to obtain a first clustering result; determining the cluster identifier to which each item latent semantic vector belongs based on the first clustering result; and constructing a user latent semantic profile based on the cluster identifier. In this way, by clustering item latent semantic vectors, determining the cluster identifier to which each item latent semantic vector belongs based on the first clustering result, and then using the cluster identifier as a representation dimension of items to construct a user latent semantic profile, the efficiency of data processing is improved, the accuracy of user profiles is increased, and thus the accuracy of recommendation system pushes is enhanced.

Embodiments of the present application provide a data processing method and device, computer equipment and a readable storage medium. The method comprises: obtaining sample spliced media features and N-dimensional labeled interaction labels of a sample object for sample multimedia data; calling a shared network in an initial recognition model to extract shared media features associated with N media recognition tasks from the sample spliced media features; calling a dedicated network i in the initial recognition model to extract dedicated media features i from the sample spliced media features; calling a recognition network i in the initial recognition model to identify an i-dimensional predicted interaction label according to the shared media features and the dedicated media features i; and training the initial recognition model according to the N-dimensional labeled interaction labels and the N-dimensional predicted interaction labels to obtain a multi-task recognition model. The media recognition accuracy of the trained initial recognition model can be improved, and the push accuracy of the multimedia data can be improved.