Online System User Group Scoring and Storage Optimization
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Solution Overview
Problem
Conventional online systems face inefficiencies in identifying and storing user groups specified by third-party systems due to potential duplication with locally-maintained targeting criteria, limiting the relevance and monetization of content presentation.
Innovation Solution
The online system evaluates user groups by determining scores for individual users and a group score based on the efficiency of targeting criteria, storing information about groups that meet certain criteria and monetization thresholds, and periodically assessing accuracy and revenue to determine continued storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the online system stores all user groups provided by third-party systems, then the system can identify more user groups for content presentation, but storage resources are wasted on duplicative groups that overlap with locally-maintained targeting criteria
Solution Approach 1:
The patent extracts and removes duplicative user groups from the stored third-party user groups. The system compares each third-party user group against locally-maintained targeting criteria and selectively removes groups that are duplicative, keeping only unique and valuable user groups in storage.
Solution Approach 2:
The patent changes the parameter of user group information by assigning scores based on duplication metrics. User groups are evaluated against locally-maintained targeting criteria and assigned scores reflecting their uniqueness and value, with higher scores indicating less duplication and greater storage priority.
2Measurement precision
If the online system maintains detailed information about all user groups, then targeting accuracy can be improved, but the complexity of managing and evaluating user group information increases
Solution Approach 1:
The patent simplifies user group management by transforming detailed user group information into scalar score values. Each user group is evaluated and assigned a score based on duplication metrics and targeting criteria, reducing complex information to manageable numerical parameters that facilitate efficient comparison and decision-making.
Solution Approach 2:
The system implements feedback mechanisms where user group scores are continuously evaluated and updated based on their performance in content presentation and monetization. This feedback loop allows the system to automatically adjust which user groups are maintained in storage based on their actual value, reducing manual management complexity.
3Productivity
If the online system stores user groups with potential duplication, then more content can be presented to users, but the relevance and monetization of content presentation decreases
Solution Approach 1:
The patent changes the parameter of user group selection by implementing score-based filtering. User groups are assigned scores reflecting their uniqueness and targeting value, and the system selectively presents content based on these scores, ensuring that content is presented to users in high-value, non-duplicative groups rather than all available groups.
Solution Approach 2:
The system extracts and removes duplicative user groups from the presentation pool. By comparing third-party user groups against locally-maintained targeting criteria and removing overlaps, the system ensures that content is presented only to users in unique, high-value groups, maintaining both productivity and reliability.
Data Source
AI summary
An online system receives information describing a target group of online system users from a third party system and determines whether to store the information describing the target group. Online system users included in the target group are identified and scores are determined for each of the identified user. A score associated with a user represents the online system's effectiveness in targeting content to the user via targeting criteria maintained by the online system. Based on the scores, the online system determines a group score associated with the target group and stores the information describing the target group if the group score satisfies one or more criteria. If the information describing the target group is stored, the online system may determine whether to continue storing the information describing the target group based on revenue obtained by the online system from presenting content based on the target group.