Distributed Content Serving via Local User Profile Generation
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Solution Overview
Problem
Existing technologies face challenges in providing privacy-preserving data analytics and content serving, particularly in ensuring user privacy while obtaining statistical information about campaign success and tracking user actions without exposing sensitive data.
Innovation Solution
The method involves obtaining offline user information from end devices, generating user profiles that match micro-segments, selecting campaigns based on these profiles, and displaying content items only when specific rules are complied with, all while maintaining user privacy by not sharing real-time user information with servers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If user information is collected and shared with servers for campaign targeting, then campaign success rates improve, but user privacy is compromised
Solution Approach 1:
The system segments user information processing between end devices and servers. End devices perform local processing of offline sensor data to generate user profiles and select campaigns, while servers only receive anonymized interaction statistics. This segmentation allows campaign effectiveness to be measured without compromising user privacy.
Solution Approach 2:
The end device acts as an intermediary that processes sensitive user information locally and only transmits anonymized campaign interaction data to servers. This intermediary role enables the system to achieve campaign success measurement while preventing direct exposure of user privacy information to servers.
2Productivity
If real-time user information is transmitted to servers for monitoring, then campaign optimization improves, but user anonymity is lost
Solution Approach 1:
The system extracts only the necessary anonymized interaction statistics from user behavior data, leaving all personally identifiable information on the end device. This extraction approach enables campaign optimization through aggregated data while maintaining user anonymity by not transmitting real-time user information to servers.
3Object-affected harmful factors
If distributed content serving is implemented at end devices, then user privacy is protected, but system complexity increases
Solution Approach 1:
The end device is empowered to perform self-service content serving operations by locally processing user profiles, selecting campaigns based on offline sensor data, and monitoring sensor activities. This self-service approach protects user privacy by keeping data processing local while managing device complexity through leveraging existing sensor capabilities and standardized processing workflows.
Data Source
AI summary
A method, system and product including obtaining offline user information at an end device, wherein the offline user information is obtained from offline sensors of the end device; based on the offline user information, generating a user profile indicating that a user of the end device matches at least one micro-segment, wherein the at least one micro-segment comprises at least one detailed population category; based on the at least one micro-segment, selecting a campaign from a set of one or more campaigns retained at a server, wherein the campaign comprises one or more rules for displaying at least one content item; monitoring the offline sensors of the end device to identify real time user activities; and upon identifying, based on the real time user activities, that a rule of the one or more rules for displaying a content item is complied with, displaying the content item in the end device.