Quotient address recommendation system and method based on multi-dimensional aggregation traffic analysis user requirements

Abstract

The invention discloses a quotient address recommendation system and method based on multi-dimensional aggregated traffic analysis user demands. The system comprises an operator SP, a merchant BS, a mobile phone traffic aggregator MA and a mobile phone user User. Supposing that the statistical range is divided into m areas, each area allows n mobile phone users at most, and the data of each user is one-dimensional, namely one mobile phone application; only one operator SP is provided and is a safe third party; the mobile phone traffic aggregator MA is used for collecting and aggregating traffic data of one mobile phone application of all regional users in real time and then sending the aggregated traffic to the operator SP; and the operator SP decrypts the aggregated traffic and then stores the aggregated traffic in different types of application databases; the merchant BS as an inquirer sends a new facility site selection query request to the operator SP, and the operator SP recommends a site selection area conforming to the merchant application type according to the new facility type of the merchant. According to the invention, the privacy information of the user is not leaked while the site selection range is recommended to the merchant, and the security of the user information is ensured.

Description

technical field [0001] The invention belongs to the technical field of big data analysis, specifically covers the technical field of user-oriented mobile phone traffic privacy protection and the technical field of location-based aggregation query, relates to a traffic aggregation method for protecting mobile phone user privacy, and analyzing user needs through multi-dimensional aggregated traffic Distribution, so as to assist merchants to find the location method of suitable area. Background technique [0002] As an essential tool for communication in people's daily life, mobile phones have become an indispensable part. The statistics and analysis of mobile phone traffic data not only provide users with better user experience, but also operators provide users with More accurate and effective marketing methods. However, the uploaded traffic data requires real-time monitoring of user traffic usage, which contains a lot of user privacy information, such as when the user is usi...

AI Technical Summary

Problems solved by technology

[0005] Most of the existing multi-dimensional aggregation schemes are used in the protection of user power data in smart grids, and do not reflect practical value from other aspects

Secondly, there are not many privacy protection applications based on mobile phone traffic, and the existing location selection schemes have not proposed in terms of the size of the aggregated data.

[0006] The existing location selection schemes are generally location-based selection methods. This method must obtain the location information of potential customers of the merchant, and the operator will also obtain the location information of mobile phone users. This requires both parties to ensure the location privacy information of their respective users. , and the two parties cannot share user information, this process is very complicated

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