Similarity Cohort Content Delivery with User Voting
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Solution Overview
Problem
Current content and advertising delivery systems rely heavily on user data collection without user knowledge or consent, failing to provide users with control over their information and compensation for its use, and do not effectively respond to users' immediate preferences.
Innovation Solution
A system that allows users to request content based on similarity with other users, using a voting mechanism to select and deliver targeted content, where users are rewarded for their participation and their data is used with their permission, grouping users dynamically based on similarity metrics such as environment and domain activity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user data is collected without user knowledge or consent, then content delivery accuracy is improved, but user privacy and trust deteriorate
Solution Approach 1:
The patent inverts the traditional approach by allowing users to actively opt-in to data sharing rather than passively having data collected. Users control what information is shared and with whom, flipping the power dynamic from platform-centric data collection to user-centric data sharing.
Solution Approach 2:
The patent introduces an intermediary layer between data collection and content delivery through the use of similarity cohorts and voting mechanisms. This intermediary structure allows for anonymized group-based targeting that preserves privacy while maintaining delivery accuracy.
2Productivity
If traditional data collection methods are used, then content delivery scale is improved, but user engagement and trust deteriorate
Solution Approach 1:
The patent enables users to self-manage their data sharing preferences and control their participation in similarity cohorts. Users can independently adjust their privacy settings and data sharing choices without requiring platform intervention or complex configuration.
Solution Approach 2:
The patent implements feedback loops where user preferences and voting behavior directly influence content delivery decisions. The system continuously adapts to user feedback through the voting mechanism, improving engagement while maintaining scale.
3Productivity
If user information is used without compensation, then content delivery efficiency is improved, but user motivation to provide accurate information deteriorates
Solution Approach 1:
The patent establishes preliminary compensation agreements and user incentives before data is collected or used. Users are compensated in advance for allowing data usage, which motivates them to provide accurate and honest information from the outset.
4Device complexity
If static user profiles are used, then system complexity is reduced, but responsiveness to user preference changes deteriorates
Solution Approach 1:
The patent transforms static user profiles into dynamic similarity cohorts that automatically update based on user voting behavior and preference changes. The system dynamically reconfigures cohort memberships as users express new preferences, maintaining low complexity through automated processes.
Data Source
AI summary
A computer-based content delivery method includes receiving from a first user a request for content; based on said request, delivering particular content to said first user, wherein said particular content was selected based on information associated with a second user distinct from said first user. The first second users are members of a similarity group, and the second user is a leader of said group and said first user is a follower in said group.