Dynamic Program Guide for Personalized Content Discovery
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Solution Overview
Problem
The increasing amount of multimedia and user-generated content from various sources makes it difficult for users to find interesting content, as conventional program guides primarily focus on commercial content and lack effective recommendations for non-commercial, user-generated material.
Innovation Solution
A server-based system that generates a dynamic, personalized program guide by combining user preferences, device capabilities, and real-time information to prioritize content recommendations, integrating both commercial and user-generated content, and allowing social interaction through content forwarding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional program guides are used to display content, then commercial content can be organized and accessed, but user-generated content from non-commercial sources becomes difficult to find and recommend
Solution Approach 1:
The program guide is segmented into multiple layers: a condensed guide showing only top-ranked recommendations and a full guide providing complete content listings. This segmentation allows the system to manage overwhelming amounts of user-generated content by prioritizing what is most relevant to each user while maintaining access to the complete dataset.
Solution Approach 2:
The patent introduces intermediary components including a message handler that receives recommendations from multiple sources, a recommender system that processes and ranks content, and social connection data that mediates between users and content. These intermediaries filter and organize user-generated content before presentation, making it discoverable without overwhelming the user interface.
2Adaptability or versatility
If a comprehensive program guide includes all available content, then users have access to maximum content variety, but the guide becomes overwhelming and difficult to navigate
Solution Approach 1:
The program guide adapts its content presentation based on local user characteristics including geographic location, social connections, and personal preferences. Each user receives a customized condensed guide that highlights content most relevant to their specific context, while the full guide remains available for users seeking broader content variety. This local quality approach ensures ease of operation for each user while maintaining overall system versatility.
Solution Approach 2:
The program guide dynamically adjusts between condensed and full views based on user interaction patterns, device capabilities, and content freshness. The condensed guide automatically updates with new recommendations from social connections and trusted sources, while the full guide provides static comprehensive listings. This dynamic adaptation allows the system to maintain both content variety and ease of navigation.
3Reliability
If program guides rely on traditional broadcaster transmissions, then commercial content delivery is reliable, but user-generated content from diverse sources cannot be effectively integrated
Solution Approach 1:
The program guide system is designed with multi-functionality to handle diverse content sources. The message handler can receive recommendations from multiple sources including social connections, trusted recommenders, and content providers. The system universally processes these different sources through a common ranking and filtering mechanism, ensuring reliable content delivery while maintaining adaptability to various content types and sources.
Solution Approach 2:
The system implements feedback mechanisms where user interactions with recommended content are tracked and used to refine future recommendations. The recommender system continuously learns from user behavior patterns, content engagement metrics, and social connection feedback to improve the reliability of content delivery while adapting to user preferences and content source characteristics.
Data Source
AI summary
A server 10 generates a program guide from a content database 20. The data base contains content descriptions including an identification of the content and the recommender of that content, which may be obtained from messages 12. A dynamic resource server 22 obtains dynamic information relating to at least one user including details of which devices, if any, are presently being used by the user as well as properties of devices associated with the user. A program guide generator 24 produces a program guide from the content descriptions and from the dynamic information, and outputs the program guide.