Dynamic Digital Media Queue Programming via Contextual Event Search
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Solution Overview
Problem
Users are overwhelmed with digital media content recommendations that do not meet their demands, as existing systems fail to effectively personalize digital media queues based on current location and date-specific events.
Innovation Solution
A method and system for programming a dynamic digital media queue that receives requests from electronic devices, determines current location and date, searches for relevant events, and recommends digital media items based on these factors, incorporating personal media libraries and providing reasons for recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing systems provide digital media content recommendations, then users receive content suggestions, but the recommendations do not meet user demands and fail to personalize based on location and date-specific events
Solution Approach 1:
The system performs preliminary actions by determining the user's current location and date before generating recommendations. It searches for date-specific events and location-relevant content in advance, preparing personalized recommendation data before the user requests content, thereby improving both personalization capability and recommendation quality.
Solution Approach 2:
The system applies local quality by tailoring recommendations to the user's specific location and date context. Different locations and dates receive different personalized content based on local events and relevance, making the recommendation system adaptable to specific circumstances while maintaining high quality through context-aware selection.
2Adaptability or versatility
If the system searches for events based on current date and location, then personalized recommendations are generated, but this increases system complexity
Solution Approach 1:
The system segments the recommendation process into distinct modules: determining current location, determining current date, searching for date-specific events, and generating personalized recommendations. This segmentation allows each function to be handled independently, managing system complexity while maintaining context-aware personalization capabilities.
Solution Approach 2:
The system uses an intermediary approach by introducing a programming server that coordinates between the electronic device and multiple data sources (location services, event databases, media libraries). This intermediary manages the complexity of integrating multiple functions while providing a unified personalized recommendation output.
3Reliability
If the system provides detailed recommendation reasons based on location and events, then user satisfaction improves, but information processing requirements increase
Solution Approach 1:
The system extracts only the essential information needed for personalized recommendations: current location, current date, and relevant date-specific events. By taking out only these critical data elements rather than processing all available information, the system reduces data processing load while still providing sufficient context for generating satisfying personalized recommendations with explanatory reasons.
Data Source
AI summary
A method and/or system for programming a dynamic digital media queue may include receiving, from an electronic device, a request for a digital media queue. The request may comprise request data. In response to the request, a search of one or more events may be performed. The search of the one or more events may be based on a current date, a current location of the electronic device and/or the request data. One or more digital media items may be determined based on the search. A recommended digital media queue may be determined. The recommended digital media queue may comprise one or more recommended digital media items. Recommendation data may be sent to the electronic device. The recommendation data may comprise the recommended digital media queue and one or more reasons explaining why the recommended digital media queue comprises the one or more recommended digital media items.