Personalized EPG via Calendar Data Analysis
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Solution Overview
Problem
Content delivery platforms lack the customization and simplicity provided by traditional television broadcast mediums, failing to account for users' schedules and individual preferences in content delivery.
Innovation Solution
A personalized auto-generated electronic programming guide (EPG) is created by obtaining user preferences, analyzing their calendar data, and selecting content items based on user preferences, location, and social network content ratings, to schedule and display content in a user-friendly format.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional television broadcast medium is used, then content delivery is simple and efficient, but customization and adaptation to user preferences is limited
Solution Approach 1:
The system automatically generates personalized EPG by analyzing user calendar data and preferences without requiring manual input from the user. The electronic programming guide self-adjusts content scheduling based on extracted calendar information, time slot preferences, and content type preferences, thereby maintaining simplicity while achieving customization.
Solution Approach 2:
The system changes the parameters of content delivery by dynamically adjusting scheduling based on user-specific parameters extracted from calendar data. Time slots, content types, and scheduling frequencies are modified according to individual user preferences and calendar patterns, enabling customized delivery while maintaining ease of use.
2Ease of manufacture
If television broadcast medium is used, then content scheduling is straightforward, but it cannot account for user's schedule and individual preferences
Solution Approach 1:
The system performs preliminary analysis of user calendar data and preferences before content scheduling occurs. By extracting and analyzing calendar information in advance, the system pre-determines optimal content scheduling that aligns with user preferences, making the scheduling process simple while ensuring it accounts for individual user needs.
Solution Approach 2:
The system incorporates feedback loops where user calendar data and preferences are continuously analyzed and used to adjust content scheduling. This feedback mechanism ensures that the scheduling system adapts to user preferences while maintaining ease of scheduling through automated adjustments based on real or historical user behavior patterns.
3Adaptability or versatility
If personalized EPG is generated based on user calendar and preferences, then user satisfaction is enhanced, but system complexity increases
Solution Approach 1:
The system introduces an intermediary processing layer that handles the complexity of calendar data analysis and preference extraction separately from the main content delivery function. This intermediary module processes calendar data, extracts preferences, and generates scheduling recommendations, thereby enabling personalization while isolating complexity in a dedicated processing layer.
Solution Approach 2:
The system creates a simplified representation or copy of user calendar data and preferences that can be processed to generate EPG scheduling. By working with a simplified model or copy of the complex user data, the system achieves personalization while managing complexity through abstraction and representation rather than direct manipulation of raw complex data.
Data Source
AI summary
A personalized auto-generated electronic programming guide for content delivery platforms is presented. A method to create a personalized auto-generated electronic programming guide (EPG) for content delivery platforms is also provided. The method can include obtaining, by a computing device, user preferences for content to be scheduled for a user, the user preferences including a type of content and a preferred time to view the type of content. The method can also include identifying one or more content items of a content hosting service that satisfy the user preferences and scheduling the identified one or more content items according to the user preferences. The method can also include presenting information about the scheduled one or more content items in a personalized EPG and providing the personalized EPG for display to the user.