Multimedia Recommendation via User Collection Analysis
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Solution Overview
Problem
Current multimedia systems lack the ability to effectively recommend media content that matches a user's preferences by analyzing their specific collection of media content and comparing it with external channels, leading to inefficiencies in finding well-matched streaming options.
Innovation Solution
A computer program product and system that determine media content characteristics of a user-specific collection, compare them with external media content channels, and present identifiers of matching channels on a multimedia player interface, allowing for automatic storage of presets and dynamic user input-based recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system analyzes user-specific collection characteristics and compares with external channels to generate recommendations, then the relevance and accuracy of recommended channels is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The system segments the media content analysis into distinct modules: user collection analysis, external channel analysis, and comparison/recommendation generation. This segmentation allows complex analysis to be performed in manageable parts, improving accuracy while reducing overall system complexity through modular architecture
Solution Approach 2:
The patent introduces an intermediary comparison module that bridges user collection characteristics and external channel characteristics. This intermediary layer processes and compares the two datasets, generating recommendations without requiring direct complex interaction between all system components, thus reducing overall system complexity
2Ease of operation
If the system automatically stores channel identifiers as preset settings, then user convenience and time-saving is improved, but the loss of user control and customization options increases
Solution Approach 1:
The system performs self-service by automatically analyzing user collections and generating channel recommendations without requiring manual user input for each recommendation. The automatic storage of preset settings eliminates repetitive manual configuration, improving convenience while maintaining user customization through optional overrides
Solution Approach 2:
The preset settings are dynamic rather than static - they can be automatically generated, modified, or overridden by user input. The system adapts between automated operation for convenience and manual control for customization, allowing the interface to dynamically adjust based on user needs and preferences
3Productivity
If the system determines media content characteristics through text matching, then the processing speed and efficiency is improved, but the measurement precision and accuracy of characteristic identification decreases
Solution Approach 1:
The system uses text matching to identify partial characteristics quickly and efficiently, then supplements this with additional analysis methods to achieve the required precision. This partial action approach allows rapid initial processing while maintaining accuracy through complementary techniques
Data Source
AI summary
A computer program product, tangibly embodied on a computer readable medium, includes instructions, which when executed by a data processor of a multimedia player, cause the data processor to determine first media content characteristics that characterize a user-specific collection of media content; compare the first media content characteristics with second media content characteristics that characterize a first set of external media content channels; and based on the results of the comparison, present identifiers of a subset of the first set of external media content channels on an interface of the multimedia player.