Advertisement recommendation method and system based on machine learning

Abstract

The embodiment of the invention discloses an advertisement recommendation method and system based on machine learning, and the method comprises the following steps: user behavior tracking: tracking the Internet behavior of each user, and mining and analyzing the real-time demands of each user; recommendation object classification: classifying recommendation objects into minimum units according toproject classification, and preliminarily establishing a mapping relationship between user real-time demands and the minimum units of the recommendation objects; recommendation object updating: updating the real-time demands of the user in real time according to the click rate of the minimum unit of the recommendation objects, and ranking the sequence list of the recommendation objects again; userdemand expansion: performing neural network topology on all real-time demands according to the click rate ranking of the minimum unit of the recommended objects, and updating the real-time demands ofeach user in real time; according to the scheme, different types of advertisement weights are distinguished in different time periods, so that the influence of search content types caused by work reasons on basic interest contents is avoided, and the accuracy and effectiveness of advertisement recommendation are improved.

Description

technical field [0001] Embodiments of the present invention relate to the technical field of recommendation systems, and in particular to a machine learning-based advertisement recommendation method and system. Background technique [0002] The value of machine learning is mainly concentrated in the steering of data and the information processing ability of data. In today's industrial development, the arrival of the era of big data has brought better technical support for data conversion, data processing and data storage. Industrial upgrading and the birth of new industries have formed a driving force that enables big data to Automatic planning for programs that can discover things, and coordination between human users and computer information. [0003] At present, with the development of Internet technology, obtaining information, life, entertainment and work through the Internet has become a part of people's life. In order to increase popularity and promote products, mer...

AI Technical Summary

Problems solved by technology

[0008] To this end, the embodiment of the present invention provides a machine learning-based advertisement recommendation method and system to solve the problem of the concentration and simplification of advertisements corresponding to user browsing records in the prior art, and the advertisement recommendation can only be passively waited for by the user's search. Unified analysis of all advertising click-through rates every day, resulting in the lack of real-time and effectiveness of recommended content

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