Contextual Relevance Engine for Activity Feed Prioritization
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Solution Overview
Problem
As a user's social network grows, the volume of activity feeds becomes overwhelming, making it difficult to distinguish important from unimportant information.
Innovation Solution
A method implemented on a computing device determines the relevance of activity feeds based on user context, prioritizing and prominently displaying those deemed most relevant, using a contextual relevance engine that considers user activity, preferences, and environmental variables.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If activity feeds are displayed without filtering or prioritization, then all activity information is provided to the user, but the user becomes overwhelmed and cannot distinguish important from unimportant information
Solution Approach 1:
The patent segments activity feeds into different priority levels (high, medium, low relevance) based on user context analysis. This segmentation allows the system to maintain complete information availability while organizing it into distinguishable categories that help users prioritize their attention.
Solution Approach 2:
The patent applies local quality by providing different display treatments to different activity feeds based on their relevance to the user's current context. High-relevance activities receive prominent display with detailed information, while low-relevance activities are summarized or hidden, creating varying information densities in different parts of the interface.
2Loss of information
If all activity feeds are displayed equally, then no information is lost, but the device complexity increases to manage and display large volumes of data
Solution Approach 1:
The patent performs preliminary analysis of user context (current activities, preferences, environmental variables) before displaying activity feeds. This preliminary action enables the system to pre-categorize and prioritize feeds, reducing the complexity of real-time data management during display.
Solution Approach 2:
The patent changes the parameter of information presentation by dynamically adjusting display priorities based on user context parameters. Instead of managing all feeds equally, the system modifies display parameters (visibility, prominence, detail level) based on relevance scores derived from contextual analysis.
3Ease of operation
If activity feeds are prioritized based on user context, then important information is easily identified, but the system requires complex analysis of user activities and environmental variables
Solution Approach 1:
The patent implements a multi-functional context analysis system that simultaneously evaluates multiple user attributes (current activities, historical preferences, environmental context) through a single integrated relevance determination process. This universal approach consolidates multiple analysis functions into one cohesive system.
Solution Approach 2:
The system uses feedback loops where user interactions with prioritized feeds are analyzed to refine future prioritization. The context analysis mechanism learns from user behavior patterns, adjusting relevance determination algorithms based on feedback about which prioritizations were most useful to the user.
Data Source
AI summary
A method for determining relevance for activity feeds is disclosed. Activity feeds are received from one or more business entities. Information is received regarding activities being performed by a user. Context information is received regarding the user. A user context is determined from the information the regarding activities being performed by the user and the context information. The user context indicates the current status of the user. A relevance of the activity feeds is determined based on the user context. At least some of the activity feeds are displayed on a computing device. The at least some of the activity feeds are displayed according to a priority determined by the relevance.