Adaptive Channel List Generation via Biometric User Identification
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Solution Overview
Problem
Current content presentation systems lack the ability to efficiently identify users and adapt to their viewing preferences, leading to a cumbersome experience due to the need for manual input and inability to share information across different devices and platforms, especially as the number of available channels and content sources increases.
Innovation Solution
A system and method that determine a user's identity through biometric information, collect and analyze channel usage data to create personalized preferred channel lists, and enable seamless switching between content signals and modes of delivery, while sharing user information across connected devices to optimize content presentation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the number of available channels increases, then content variety is improved, but channel surfing efficiency deteriorates
Solution Approach 1:
The system pre-arranges channels in a preferred order based on user viewing history and preferences before the user needs to access them. This preliminary organization eliminates the need for users to manually search through channels, directly resolving the time loss problem while maintaining channel variety.
Solution Approach 2:
The system automatically updates and reorders the preferred channel list based on user viewing patterns without requiring manual user input. The system serves itself by learning from user behavior and adapting the channel arrangement, thereby maintaining efficiency as channel numbers increase.
2Quantity of substance
If channel assignments are rearranged to accommodate new programming, then content variety is improved, but user navigation complexity increases
Solution Approach 1:
The system pre-rearranges channels in the preferred list according to user preferences and viewing history before users need to access them. This preliminary reorganization ensures that even when channel assignments change, users immediately see their preferred channels in familiar positions without needing to learn new channel numbers or navigate structures.
Solution Approach 2:
The system maintains different ordering arrangements for different user groups or contexts. By applying local customization to channel arrangement based on individual user preferences, the system preserves ease of navigation for each user while accommodating overall channel reassignments for new content.
3Device complexity
If manual channel selection is required, then system simplicity is improved, but user interaction efficiency deteriorates
Solution Approach 1:
The system automatically learns user preferences and generates the preferred channel list without requiring manual user input or configuration. This self-service approach maintains system simplicity from the user perspective while dramatically improving channel access speed, as users simply receive their personalized channel order without needing to manually arrange or select channels.
Solution Approach 2:
The system uses feedback from user viewing behavior to automatically adjust and update the preferred channel list. By monitoring which channels users watch and in what order, the system continuously refines the arrangement, improving productivity over time while keeping the interface simple and requiring no manual user configuration.
4Device complexity
If user information is stored locally on each device, then system simplicity is improved, but information sharing capability deteriorates
Solution Approach 1:
The preferred channel list and user profile information are designed to be universally accessible across multiple devices and platforms. The system implements a centralized or cloud-based storage mechanism that allows the same personalized channel arrangement to be accessed whether the user is at home, traveling, or using different devices, thereby enabling information sharing while maintaining system simplicity through a unified approach.
Data Source
AI summary
Systems and/or methods are disclosed herein to identify a user interacting with a content presentation system, adaptively learn, in a passive manner, a user's pattern of accessing content over time, and globally store the user's identifying and use information. Specifically, systems and/or methods for creating a preferred channel list, including determining an identity of a user interacting with a content presentation system, collecting channel use information for each of a plurality of channels from the user's interaction with the content presentation system, storing the channel use information, determining a value for each of the plural channels as a function of the channel use information, and creating a preferred channel list for the plural channels as a function of the determined value.