Content Engine for Predicting User Interest in Media
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Solution Overview
Problem
Consumers face difficulty in identifying and accessing media content of interest due to the vast and diverse range of electronic media available, which existing technologies have not effectively addressed.
Innovation Solution
A method and system that utilize a content engine in a television receiver to analyze user preferences and viewing habits, predict user interest, and provide access to priority media content by monitoring and comparing current media being watched with other available content, offering recommendations or automatic switching to more appealing content based on user profiles and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If consumers access a vast amount of available media content, then content diversity and flexibility are improved, but the difficulty of identifying content of interest increases
Solution Approach 1:
The system continuously monitors user viewing habits and preferences, using this feedback to dynamically generate and update user profiles. These profiles then guide the recommendation engine to suggest relevant content, creating a closed-loop system that improves content identification accuracy over time while maintaining access to diverse content libraries
Solution Approach 2:
The system automatically analyzes user behavior patterns and generates personalized content recommendations without requiring manual input from users. The television receiver autonomously profiles user preferences by monitoring viewing habits and uses this information to identify and present relevant content, eliminating the need for users to manually search through vast content libraries
2Measurement precision
If the system monitors and analyzes user viewing habits to predict interest, then content recommendation accuracy is improved, but device complexity increases
Solution Approach 1:
The television receiver performs multiple functions: it serves as the primary display device, simultaneously acts as a content analyzer by monitoring viewing habits, generates user profiles, and functions as a recommendation engine. This multi-functionality consolidates what could be separate complex systems into a single integrated device, managing complexity while improving recommendation accuracy
3Ease of operation
If the system provides automatic access to priority media content, then user convenience is improved, but loss of current media content context increases
Solution Approach 1:
The system proactively identifies and prepares priority content recommendations before users explicitly request them. By continuously analyzing viewing patterns and pre-generating recommendations based on detected interest, the system has relevant content ready when users might want to switch, reducing the time and effort needed for content transitions while maintaining user convenience
Data Source
AI summary
System and methods for providing access to particular media content. First media content may be output for presentation by a display device. Second media content other than the first media content may be monitored. A determination may be made as to whether the second media content has a priority greater than the first media content. Access to the second media content for presentation by the display device may be provided.