Personalized Content List Reordering for Set-Top Box
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Solution Overview
Problem
Users face difficulty in selecting content from a vast number of channels and timeslots in traditional grid guides, leading to missed opportunities for viewing content that is not pre-scheduled for recording.
Innovation Solution
A system and method for displaying personalized content recommendations, where a user device identifier is used to reorder content lists based on user viewing habits, allowing for dynamic display of recommended content on a set-top box, including 'What's On' and 'You Might Like' lists, which can automatically record content without user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a traditional grid guide displays all channels and timeslots, then complete content information is provided to users, but the interface becomes overwhelming and difficult to navigate
Solution Approach 1:
The patent extracts and separates the most relevant content information from the complete grid guide, presenting it in a focused recommendation list format. This allows the system to highlight key content (such as recorded programs and personalized recommendations) without requiring users to navigate through the entire channel and timeslot matrix, thus maintaining information completeness while improving ease of operation.
Solution Approach 2:
The patent segments the overwhelming grid guide information into distinct, manageable sections: a recommendation list showing recorded content and personalized suggestions, and the full grid guide accessible through navigation. This segmentation allows users to quickly access important information without being confronted by the complete set of channels and timeslots simultaneously.
2Reliability
If users manually preschedule content for recording, then recording accuracy is high, but users may miss content that is not pre-scheduled
Solution Approach 1:
The patent implements an automated recommendation system that analyzes user viewing patterns and automatically generates recording recommendations without requiring manual user input. The system serves itself by identifying content worth recording based on user behavior data, thereby maintaining high recording accuracy for important content while expanding flexibility to capture content that users might otherwise miss.
Solution Approach 2:
The patent employs feedback mechanisms where user viewing habits are continuously monitored and analyzed to refine recording recommendations. This feedback loop allows the system to adapt to user preferences over time, improving both the reliability of recording decisions and the versatility of content capture by learning from actual user behavior rather than relying solely on manual scheduling.
3Ease of operation
If the system displays personalized recommendations, then user experience is improved, but system complexity increases
Solution Approach 1:
The patent changes the parameters of content display from static channel listings to dynamic personalized recommendations based on user viewing patterns. By analyzing user behavior data and adjusting recommendation parameters accordingly, the system improves user experience while managing complexity through focused data processing on key viewing metrics rather than comprehensive analysis of all possible content variables.
Data Source
AI summary
A system and method for operating the same includes a memory and a controller that stores content in the memory to form stored content. The controller receives a display request for displaying content from a user device through a network. The display request comprises a user device identifier. The controller determines a timeslot corresponding to the display request, retrieves a content list corresponding to stored content, reorders the content list in response to the timeslot and the user device identifier to form a reordered list and communicates the reordered list to the user device.


