Personalized marketing recommendation system

Abstract

The invention discloses a personalized marketing recommendation system. The system comprises a receiving engine for receiving a recommendation request and enabling a receiving queue, a central control engine in charge of mutual communication and resource coordination among components, a client identification engine for identifying all subject information of a current client according to input client subject information, a calculation engine for comprehensively calculating commodities most suitable for recommendation in a current recommendation column, a data engine for obtaining client information and product information and preferentially using a redis cache, a display engine for extracting display field information and matching a personalized display template, a pushing engine for pushing recommendation information to each pushing channel, and a data mining engine for constructing a full view tag of a user. According to the system, multiple user identity labels of multiple channels can be identified; scene pushing of different channels can be adapted; different types of businesses are recommended by adopting a heuristic recommendation algorithm; the business conversion rate and the user satisfaction are improved; and the performance requirements of low-delay recommendation, easy expansion and the like can be met.

Description

technical field [0001] The invention relates to the technical field of marketing recommendation systems, in particular to a personalized marketing recommendation system. Background technique [0002] The marketing recommendation system is a medium that connects users and items. Its main job is to identify user characteristics when a user arrives in a business scenario, and then find items related to each characteristic for each characteristic, thereby finally generating a user's recommendation list. [0003] The existing marketing recommendation system includes two implementation methods, please refer to figure 1 and figure 2 , figure 1 It is a schematic diagram of the first implementation mode of the existing marketing recommendation system, figure 2 It is a schematic diagram of the second implementation mode of the existing marketing recommendation system. [0004] The recommendation system architecture of the first implementation mode of the existing marketing recom...

AI Technical Summary

Problems solved by technology

[0013] The two implementations of the existing marketing recommendation system are mainly personalized recommendation systems in the station, which are suitable for e-commerce websites, information media and social networking sites. The applicable channel is single and cannot meet the requirements of multi-channel and full-service personalized recommendation; , most recommendation engines do not have the function of customer identification, the identification method for customers is single, and cannot make full use of customer information to make effective recommendations; moreover, traditional recommendation systems generally do not have easy scalability and configuration backup systems. When the system fails, there is no timely Effective buffers or workarounds, lacking some level of rigor

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