Audiovisual Decoder Emotion-Based Program Recommendation
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Solution Overview
Problem
Current audiovisual program recommendation systems fail to account for users' emotional states, leading to irrelevant program suggestions, as they primarily rely on popularity and category-based recommendations.
Innovation Solution
A method that associates genres with emotional states using priority and counting tables to sort and recommend programs based on user emotional states, updating counters upon program selection, and displaying a list of programs prioritized by relevance to the user's emotional state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If program recommendations are based on popularity and category, then the recommendation system is simple and easy to implement, but the relevance of recommended programs to user needs deteriorates
Solution Approach 1:
The patent changes the parameters used for recommendation from static popularity and category data to dynamic emotional state data. By detecting user emotional states and associating them with genre preferences, the system adapts recommendations to real-time user needs, resolving the contradiction between system simplicity and recommendation relevance.
Solution Approach 2:
The system implements feedback by continuously monitoring user emotional states and using this information to adjust recommendations. The emotional state detection creates a closed-loop system where user responses (emotional states) feed back into the recommendation algorithm, improving relevance over time while maintaining manageable complexity through automated feedback processing.
2Ease of manufacture
If program recommendations are based on popularity and category, then the system is easy to implement, but user satisfaction deteriorates
Solution Approach 1:
The system performs self-service by automatically detecting user emotional states and generating personalized recommendations without requiring manual user input or configuration. The automated emotion detection and genre association handles the complexity of personalization, maintaining ease of implementation while significantly improving user satisfaction through tailored recommendations.
3Device complexity
If program recommendations do not consider emotional state, then the system remains simple, but adaptability to user needs deteriorates
Solution Approach 1:
The patent introduces an intermediary layer between the simple recommendation system and user needs: the emotional state detection module. This intermediary captures real-time user emotional information and translates it into genre preferences, enabling the system to adapt to user needs without fundamentally redesigning the core recommendation architecture, thus maintaining simplicity while improving adaptability.
Data Source
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AI summary
The present invention relates to a method and an audiovisual decoder (10) for recommending a list of at least one audiovisual program to at least one user, the program(s) being categorized by genre and/or subgenre. According to the invention, the method (100) comprises the steps performed by said audiovisual decoder (10): - associating (E20) said genres/subgenres with emotional states; - detecting (E40) a current emotional state of said at least one user; - sorting (E60) said programs from said catalog, taking into account at least said detected emotional state and the genres and/or subgenres associated with said detected emotional state; - displaying (E80) a list of at least one audiovisual program, taking into account said sorting of said programs from said catalog. In this way, the invention makes it possible to take into account the detected current emotional state of the user in order to improve the relevance of the programs recommended to them.