Client Device Redundant Digital Component Filtering
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Solution Overview
Problem
Conventional systems fail to prevent the repetitive presentation of digital components to users across multiple content platforms, leading to wastage of computing resources and inefficient use of display space, as they do not account for user interactions and affirmative actions with digital content.
Innovation Solution
A client device stores a list of digital components and uses machine learning models to detect affirmative user actions, modifying the list by lowering the rank or removing components that have already been interacted with, and sends this modified list to content providers to prevent redundant content from being displayed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional systems present digital components across multiple content platforms, then content providers can maximize their content delivery, but users experience repetitive content and computing resources are wasted
Solution Approach 1:
The system performs preliminary actions by storing a list of digital components and user interaction data on the client device before content requests are made. When a content request is received, the system proactively filters out digital components with which the user has already had affirmative actions, preventing redundant content delivery before it occurs. This preliminary filtering mechanism resolves the contradiction by preparing the filter list in advance and applying it automatically to block repetitive content while maintaining efficient content delivery for new components.
2Adaptability or versatility
If conventional systems display all available digital components, then content providers can maximize their visibility, but display space is used inefficiently
Solution Approach 1:
The system applies local quality by implementing content filtering specifically at the client device level where user interaction data is stored. The filter mechanism operates locally to modify the list of digital components based on user-specific affirmative actions, ensuring that only relevant new components are displayed. This localized filtering resolves the contradiction by maintaining comprehensive content provision capabilities while optimizing display space utilization by excluding only the specific redundant components that the user has already interacted with.
3Productivity
If user interaction data is shared with content providers, then redundant content can be filtered, but security and privacy are compromised
Solution Approach 1:
The system introduces an intermediary mechanism by storing and processing user interaction data locally on the client device rather than sharing it directly with content providers. The client device acts as an intermediary that automatically filters digital components using the stored interaction data and sends only the filtered list to content providers. This intermediary approach resolves the contradiction by enabling effective redundant content filtering through local data processing while maintaining security and privacy by preventing direct exposure of user interaction data to third parties.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for limiting provision and display of redundant digital components on a client. Methods can include storing, by a client device, a list of digital components specifying digital components available for provision to the client device. For a first digital component received within a first application, the client device detects a set of signals specifying a first user interaction with the first digital component and a second user interaction with content provided in response to the first user interaction. Based on whether an affirmative user action was performed, the client device can modify the list of digital components. When a request to access a content page within a second application is received, the client device can receive the second digital component, which can be selected from among digital components included on the modified list of digital components.