Directed Graph Content Scheduling for Personalized Viewing
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Solution Overview
Problem
The vast availability of content through scheduled broadcasts and on-demand systems presents a navigational challenge for both viewers and content providers, as existing methods require significant user interaction or fail to tailor content effectively to individual preferences.
Innovation Solution
A method involving a directed graph schedule that adapts based on viewer interaction, such as previously viewed content, satisfaction, and location, allowing for dynamic content presentation without requiring explicit user input, using a client device to traverse the graph and pre-cache content for efficient delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a vast number of television channels and VOD content are made available to viewers, then content variety and availability are improved, but navigational complexity and difficulty in finding relevant content increase
Solution Approach 1:
The system automatically generates personalized schedules without requiring active user navigation or input. The client device autonomously receives state information, traverses the directed graph, and assembles content sequences tailored to viewer preferences, eliminating the need for complex manual navigation through vast content libraries.
Solution Approach 2:
A directed graph schedule structure acts as an intermediary between the vast content library and the viewer. This graph organizes content into nodes and paths, mediating the connection by pre-structuring navigation logic so viewers receive personalized schedules without directly navigating the underlying complexity of content availability.
2Ease of operation
If traditional broadcast schedules are used where all viewers receive the same content sequence, then system simplicity is maintained, but personalization and viewer preference adaptation are lost
Solution Approach 1:
The system applies local quality by customizing content sequences for individual viewers while maintaining the same underlying directed graph structure. Each viewer receives a personalized schedule based on their specific state information (preferences, location, viewing habits), allowing personalization without requiring different system architectures for different users.
Solution Approach 2:
The schedule transitions from static traditional broadcast sequences to dynamic personalized sequences. The system continuously adapts content presentation by traversing the directed graph based on real-time state information and viewer interactions, enabling the schedule to change and adapt while viewers consume content.
3Adaptability or versatility
If video on demand systems allow users to select and watch content immediately, then viewing flexibility is improved, but user interaction requirements and complexity increase
Solution Approach 1:
The system performs automatic content selection and sequencing without requiring active user choices. The client device autonomously traverses the directed graph and assembles personalized schedules based on pre-configured state information, eliminating the need for users to manually search, select, and manage content while still providing personalized viewing experiences.
Solution Approach 2:
The system performs preliminary actions by pre-configuring state information and pre-structuring the directed graph schedule before content consumption. Viewer preferences, location data, and viewing habits are captured in advance, and the directed graph is prepared with multiple possible content paths, enabling automatic personalization without real-time user input.
4Measurement precision
If content schedules are dynamically adapted based on viewer interactions, then personalization quality is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The directed graph serves as a computational intermediary that simplifies the personalization process. Instead of directly processing complex viewer interaction data to generate schedules, the system uses the pre-structured directed graph as an intermediary layer that automatically translates state information into personalized content sequences, reducing processing complexity while maintaining personalization quality.
Data Source
AI summary
A method of presenting content to a viewer is described. The method includes: receiving a schedule of content at a client operable by the viewer, the schedule of content including a directed graph, the directed graph including a plurality of nodes, wherein each node in the plurality of nodes is connected to one or more other nodes in the plurality of nodes by one or more paths, wherein each path represents content presentable to the viewer; traversing the directed graph by following a route between nodes and along paths of the directed graph, wherein at each node the client determines a path to follow according to state information accessible by the client; and presenting content to the viewer as each path is followed.