Self-Adaptive Multi-User Program Guide Using Viewing History
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Solution Overview
Problem
Existing methods for personalizing program guides and DVR directories in multi-user systems are complicated and require significant user involvement, failing to dynamically adapt to the preferences of individual users within a household.
Innovation Solution
A media access device, such as a set-top box or DVR, automatically optimizes content listings based on the past viewing history of a current user, using user identification methods like remote controls, biometrics, or facial recognition to prioritize content and DVR entries initiated by that user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing methods are used to personalize program guides and DVR directories in multi-user systems, then user-specific content prioritization can be achieved, but the system setup becomes complicated and requires considerable user involvement
Solution Approach 1:
The system automatically performs user identification and content prioritization without requiring manual configuration. The media access device autonomously monitors viewing habits, identifies current users through various methods (remote control, biometrics, facial recognition), and dynamically prioritizes content listings based on observed preferences, eliminating the need for users to manually set up personalization parameters
Solution Approach 2:
The system proactively establishes user profiles and content preferences through automatic monitoring and analysis of viewing patterns before users need to access personalized content. By continuously tracking what users watch and when, the system pre-configures prioritized listings that adapt over time, removing the need for users to perform setup actions
2Adaptability or versatility
If manual configuration methods are used for user personalization, then user-specific preferences can be captured, but the ease of operation is reduced due to considerable user involvement required
Solution Approach 1:
The system automatically identifies users through multiple methods (remote control association, biometric sensors, facial recognition cameras) and self-configures content prioritization based on monitored viewing behavior. Users simply need to be present or use the remote control, while the system autonomously captures preferences and generates personalized listings without requiring users to navigate complex configuration menus
Solution Approach 2:
The system continuously monitors user viewing patterns and uses this feedback to dynamically adjust content prioritization. By tracking what users watch, when they watch it, and for how long, the system automatically refines personalized listings in real-time, making the system adapt to user preferences without requiring explicit user input or reconfiguration
Data Source
AI summary
A programming access device such as, for example, a cable or satellite set top box (STB), a digital video recorder (DVR), a personal computer, and/or a digital media receivers automatically optimizes an order of or filters content choices presented in a content listing, such as a program guide display, favorite channel display, and/or a recording listing display based on the past viewing and/or recording history of a current user or group of users.