Content Filtering Based on User Viewing Time
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face challenges in accessing relevant digital media content due to information overload and timing mismatches, leading to missed important information as current services often provide duplicate content that is not viewed at the suitable time or in a suitable format.
Innovation Solution
A method and system that filter content based on user behavior patterns, available time, and preferred formats to deliver personalized content to a user device, ensuring that relevant information is presented in a timely and suitable manner by determining user behavior patterns and available time for viewing, and selecting content based on previously viewed posts and time frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If current services provide information to consumers, then consumers can access digital media content, but consumers receive duplicate content that has already been viewed and miss relevant information due to timing mismatches
Solution Approach 1:
The system performs preliminary actions by determining user behavior patterns and available time in advance before filtering and delivering content. This allows the system to pre-process and personalize content streams based on predicted user availability and preferences, ensuring relevant information is delivered at the right time without duplication of already-viewed content.
Solution Approach 2:
The system uses feedback mechanisms by analyzing user behavior patterns from previously submitted requests and viewed content. This feedback loop enables the system to continuously improve content filtering accuracy, adapting to user preferences and timing patterns to deliver personalized content that avoids duplication and timing mismatches.
2Productivity
If services stream all available content to users, then users have access to comprehensive information, but users spend excessive time filtering through duplicate and irrelevant content
Solution Approach 1:
The system extracts and removes duplicate content and already-viewed posts from the content stream before delivery. By taking out irrelevant and redundant information, the system delivers only unique, relevant content that matches user availability, significantly improving information consumption efficiency while reducing the time users spend filtering through duplicate content.
Solution Approach 2:
The system changes parameters by dynamically adjusting content selection based on determined available time and user behavior patterns. Instead of delivering a static content stream, the system adapts content parameters (selection, timing, format) to match user availability, improving productivity while minimizing time loss through intelligent filtering.
3Reliability
If services deliver content without considering user timing, then content delivery is simple and fast, but relevant information does not reach users at suitable times
Solution Approach 1:
The system performs preliminary determination of user behavior patterns and available time before content delivery. This advance preparation enables reliable timely content delivery by ensuring content is scheduled for delivery when users are actually available, while the complexity is managed through automated pattern recognition rather than complex real-time decision-making.
4Ease of operation
If services provide unfiltered content streams, then the system complexity is low, but users cannot efficiently access relevant information in suitable formats
Solution Approach 1:
The filtering system operates autonomously by automatically determining user behavior patterns, available time, and content relevance without requiring user intervention. This self-service approach improves content accessibility by delivering personalized content in suitable formats while managing system complexity through automated decision-making algorithms that learn from user behavior.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A system and method for filtering a stream of content based on the time available to a user is disclosed. A filter application includes a timing module, a determination module and a user interface engine. The timing module receives a request for a stream of content from a user. The determination module calculates a viewing time for each post in the stream of content and determines one or more posts from the stream of content based on the viewing time of each post and an available time for the user. The user interface engine provides the one or more posts to the user.