Search-Instance Content Generation Through Privacy-Aware IP Linkage
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Solution Overview
Problem
Existing techniques for determining physical addresses for postal campaigns and ascertaining user information for online content personalization face challenges, including privacy concerns and inefficiencies in linking IP addresses to accurate geographic locations and user attributes.
Innovation Solution
A system and method for determining physical addresses and email addresses associated with IP addresses by analyzing search queries and request data, using machine learning to derive content relevance, and employing heuristic linkages to identify similar IP addresses for targeted campaigns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional techniques (cookies, device fingerprinting, mapping users to device ID) are used to ascertain user information for online content personalization, then user identification capability is improved, but privacy concerns increase and measurement precision deteriorates
Solution Approach 1:
The patent introduces an intermediary system that uses machine learning models to indirectly map IP addresses to geographic locations and user attributes without requiring direct user identification. The system processes search query data as an intermediary step to infer user characteristics, thereby maintaining privacy while improving identification accuracy.
Solution Approach 2:
The patent replaces conventional mechanical identification methods (cookies, device fingerprinting) with a machine learning-based system that analyzes search query patterns. This substitution uses computational inference rather than direct tracking mechanisms, improving both privacy protection and measurement precision.
2Measurement precision
If machine learning and heuristic linkages are used to derive content relevance and identify similar IP addresses, then campaign targeting precision is improved, but device complexity increases
Solution Approach 1:
The patent segments the complex task of user identification and campaign targeting into distinct modules: search query data collection, machine learning content relevance analysis, heuristic IP address similarity identification, and campaign matching. This segmentation manages system complexity by breaking down the overall process into manageable, independent components.
Solution Approach 2:
The system uses self-service mechanisms where the machine learning models automatically learn from search query data and the heuristic algorithms automatically identify similar IP addresses without manual intervention. This automation reduces operational complexity while maintaining high targeting precision.
3Productivity
If IP addresses are captured and analyzed from search engines, plug-ins, and Internet service providers to determine physical addresses, then postal campaign effectiveness is improved, but loss of information increases due to privacy constraints
Solution Approach 1:
The patent applies partial action by collecting and analyzing only the specific search query data necessary for determining geographic locations and user attributes, rather than capturing all possible user information. This selective data collection maintains campaign effectiveness while minimizing information loss due to privacy constraints.
Solution Approach 2:
The system changes the parameter of data collection from comprehensive user profile information to specific search query parameters. By focusing on search query content, timing, and patterns rather than personal identifiers, the system maintains productivity while reducing information loss.
Data Source
AI summary
Methods and apparatus related to determining and/or utilizing one or more attributes for an Internet Protocol (IP) address and/or other source identifier(s). In some implementations, the attributes may include a physical address and/or email address associated with the source identifier(s). Some implementations are directed to determining physical addresses for inclusion in a postal campaign and/or determining email addresses for inclusion in an email campaign. In some of those implementations, the physical addresses and/or email addresses are determined based on computing devices having source identifiers associated with those addresses having submitted searches with search content assigned to the campaign.