Personalized recommendation system and method based on deep neural network

Abstract

The invention provides a personalized recommendation system and a personalized recommendation method based on a deep neural network. The method includes: by fusing the candidate set generation moduleof the depth neural network, combining multi-user and multi-item features to conduct deep neural network learning to generate candidate sets, and based on a ranking set generation module fusing the deep neural network, combining the multi-user and multi-item features to conduct the depth neural network learning and scoring on the candidate set, to generate a better ranking set containing the personalized recommendation content, and finally, based on the collaborative filtering algorithm and the ranking set, carrying out further personalized recommendation, and obtaining the final recommendation list. Through the above way, the multi-user and multi-item are combined to improve the accuracy of a recommendation process, and accurate personalized recommendation is achieved in combination witha collaborative filtering algorithm. As a result, the personalized recommendation efficiency and user experience are improved.

Description

technical field [0001] The present invention relates to the technical field of data mining and deep learning, and more specifically, relates to a personalized recommendation system and method based on a deep neural network. Background technique [0002] With the rapid development of the modern Internet industry, Internet data has grown exponentially, and users have higher and higher requirements for the personalization, accuracy, and predictability of recommended data. Commonly used recommendation algorithms in the prior art include collaborative filtering recommendation, combination recommendation, content-based recommendation, and the like. [0003] Based on the current perception changes of Internet data, more and more user and project data are composed of multi-source heterogeneous data such as videos, images, tags, and texts. Therefore, the data content faced in the process of data recommendation is complex The speed has also increased. The recommendation algorithms c...

AI Technical Summary

Problems solved by technology

[0004] In view of this, the embodiment of the present invention provides a personalized recommendation system and method based on a deep neural network to solve the problem of low recommendation efficiency and affecting user experience in existing recommendation methods

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