Car shopping pushing method based on collaborative filtering, server and client

Abstract

The invention discloses a car shopping pushing method based on collaborative filtering, a server and a client. The car shopping pushing method comprises the following steps: receiving user transactioninformation; obtaining transaction feature information and user account information according to the user transaction information, and obtaining purchase habit information according to the user transaction information and the user account information; obtaining transaction log information, matching the purchase habit information with the transaction log information to obtain collaborative featureinformation, and filtering the transaction log information according to the collaborative feature information to obtain a collaborative filtering result; according to the commodity recommendation method and device, the technical problems that in the prior art, the shopping function applicability is low, flexibility is lacked, and commodity recommendation services are lacked of individuation are solved.

Description

technical field [0001] The invention relates to a push method, in particular to a collaborative filtering-based car-machine shopping push method, a server and a client. Background technique [0002] With the improvement of people's living standards, motor vehicles are rapidly popularized in the whole society, the number of motor vehicles in my country continues to rise, and people travel by car more and more frequently. During the driving process of the vehicle, the passengers often use mobile devices in the car to carry out entertainment activities such as shopping to pass the time. Single, unable to use intelligent means to recommend personalized products. The fixed advertisements preset by the system cannot meet the different shopping needs of the public, and it is easy to reduce the user experience of the shopping function. Passengers need to manually input and search for their favorite products, intelligent lower. In addition, when passengers use mobile devices to cha...

AI Technical Summary

Problems solved by technology

[0004] In view of the above shortcomings of the prior art, the purpose of the present invention is to provide a car-machine shopping push method based on collaborative filtering, a server and a client, which can be applied to the intelligent recommendation of shopping information on the way to solve the problems existing in the prior art. The shopping function has low applicability, lack of flexibility, and lack of personalization in commodity recommendation services. The present invention provides a collaborative filtering-based car-machine shopping push method, a server and a client, and a collaborative filtering-based car-machine shopping push method. The method is applied to a server, and the method includes: receiving user transaction information; obtaining purchase habit information according to the user transaction information; obtaining transaction log information, matching the purchase habit information with the transaction log information to obtain collaborative feature information, and processing the collaborative feature information to obtain Collaborative filtering results; extract user collaborative data from collaborative filtering results, obtain and send recommendation information based on user collaborative data

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