Missed Live Event Content Restoration by User Interest Matching
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Solution Overview
Problem
Interruptions in online streaming services cause users to miss important information during events or conferences due to network issues or scheduling conflicts, leading to inefficiencies in information delivery.
Innovation Solution
A method that identifies user interests from past interactions and profiles, categorizes information during and after an absence period, and prioritizes content delivery based on user interest intersections to restore missed information upon reconnection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users remain connected during service interruptions, then they can receive real-time content, but network resources are wasted and user experience deteriorates due to receiving irrelevant or duplicate content upon reconnection
Solution Approach 1:
The system performs preliminary actions by capturing and categorizing content during the absence period before the user returns. User profiles and interest categories are pre-established, enabling the system to pre-process incoming content and organize it by relevance categories, so that when the user reconnects, only relevant content needs to be delivered.
Solution Approach 2:
The system extracts and separates relevant content from the total content stream during the user's absence. By using user profiles and interest categories, the system identifies and extracts only the portions of content that match user interests, discarding or setting aside irrelevant content that would not be useful to the user.
2Loss of information
If all content during absence period is delivered to user upon reconnection, then no information is lost, but information overload occurs and user engagement decreases
Solution Approach 1:
The system applies local quality by differentiating content delivery based on user-specific interest categories. Different portions of the content stream are treated differently according to their relevance to specific user profiles. Content is categorized into different quality levels of importance based on matching against user interests, so that high-relevance content is delivered while low-relevance content is filtered out.
Solution Approach 2:
The system delivers only the necessary portion of content rather than all content. By using user profiles and interest categories, the system determines the optimal subset of content that satisfies user information needs without delivering excessive irrelevant content, achieving partial action that is sufficient for user requirements.
3Measurement precision
If user profile analysis is performed in real-time, then content relevance is maximized, but processing time increases and system response delays
Solution Approach 1:
User profile analysis and category establishment are performed in advance before the user's absence begins. The system pre-processes user preferences, interests, and categorization schemas, storing them for quick retrieval. This preliminary action eliminates the need for real-time profile analysis during content delivery, significantly reducing processing time while maintaining high relevance accuracy.
4Productivity
If content is categorized and prioritized based on user interest, then delivery efficiency improves, but system complexity increases
Solution Approach 1:
The content delivery system is segmented into distinct functional modules: user profile management, content capture and categorization, interest matching engine, and selective content delivery. Each module handles a specific aspect of the content delivery process, making the overall complex system manageable through modular design. Content is also segmented into different relevance categories that can be independently processed and delivered.
Data Source
AI summary
A method, computer system, and a computer program product are provided for a restoring missing content to a user that was absent during a portion of a live event. The process will identify the absence period and that is being participated by a user and obtains extracted information relating to the user that was previously gathered from a variety of sources including past user interactions and a user profile. This information is further analyzed and prioritized according to user interest priority determined by the extracted information. This information is categorized into a first set of domains. Information provided during the absence of the user will also be captured and categorized into a second set of domain categories. An intersection between the first and second set of domain categories will be found and prioritized by user interest. This will be presented to the user upon user's return.