Client-Server Content Matching for Privacy Protection
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Solution Overview
Problem
Current methods for delivering targeted advertisements and content to users on public networks, such as the Internet, raise privacy concerns as they require users to disclose detailed information about their interests, which may not accurately reflect their current preferences, and can lead to the misuse of aggregated data for tracking purposes.
Innovation Solution
A system and method that allows users to provide limited or anonymous information through a client application, which generates queries to a search server using profile information, enabling precise content selection without disclosing sensitive data, and uses metadata to refine search results on the client device, ensuring privacy and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed user information is collected to improve content targeting accuracy, then content relevance is improved, but user privacy is compromised
Solution Approach 1:
The system segments user information processing into two distinct parts: (1) Anonymous demographic data is collected and used for broad content categorization and targeting, and (2) Specific search queries and detailed user behavior remain local to the client device. This segmentation allows content relevance to be improved through demographic matching while protecting user privacy by keeping sensitive query data local.
Solution Approach 2:
The system introduces an intermediary mechanism where anonymous demographic information serves as a mediator between the user and content providers. Instead of directly sharing detailed search queries and behavior data, the system uses anonymized demographic profiles as an intermediate representation that enables targeted content delivery without exposing sensitive user information.
2Measurement precision
If user search history is aggregated to improve advertisement targeting, then ad relevance is improved, but data security is compromised
Solution Approach 1:
The system extracts only the essential demographic information needed for advertisement targeting while leaving out sensitive search history and detailed user behavior data. By taking out only the necessary anonymized demographic attributes (age, gender, location) and leaving the sensitive query data local, the system achieves ad targeting accuracy without compromising data security.
3Measurement precision
If comprehensive user profiles are created to improve content delivery precision, then content relevance is improved, but resource consumption increases
Solution Approach 1:
The system applies partial action by using only the portion of user information that is necessary for content delivery - specifically anonymized demographic data - rather than processing complete user profiles. This partial information approach achieves sufficient content relevance while significantly reducing the computational and communication resources required.
Data Source
AI summary
Methods and systems for delivering content to users are provided. More particularly, a search server applies server side profile information to perform an initial search for content. That content or metadata representing the content is returned to the client device. A client application running on the client device can then apply client side profile information to refine or filter the initial search results. Content identified through the application of the client side profile information can then be obtained if it has not already been downloaded to the client device, and presented to the user. Client side profile information can include information that the user does not wish to disclose, information regarding content currently being accessed by the user, and/or information regarding holes or space available for the presentation of content to the user.