Content Selection Engine With User-Controlled Adventurousness
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Solution Overview
Problem
Existing content distribution platforms struggle to adapt to users' rapidly changing preferences due to varying tastes and moods, leading to a challenge in consistently providing relevant content.
Innovation Solution
A computer-implemented content selection engine that utilizes a user-controllable adventurousness parameter to select and provide content items based on a baseline position and user-adjustable adventurousness settings, allowing for real-time adaptation to user preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content selection is based on fixed user preferences, then content delivery is simple and fast, but it cannot adapt to users' rapidly changing tastes and moods
Solution Approach 1:
The system implements dynamic adaptability by introducing a time-varying adventurousness parameter that users can adjust in real-time. This parameter dynamically modifies content selection from a baseline preference, allowing the system to adapt to changing user tastes without requiring complex retraining or reconfiguration. The dynamic parameter replaces static preference profiles with a flexible, user-controlled adaptation mechanism.
Solution Approach 2:
The system changes the state space of user preferences by adding a continuous adventurousness parameter that modulates the deviation from baseline preferences. Instead of storing multiple static preference profiles, the system uses parameter changes to adapt content selection, where the adventurousness parameter controls the extent of deviation from baseline, enabling simple yet effective adaptation to varying user tastes.
2Adaptability or versatility
If content selection explores diverse content items, then user discovery increases, but user satisfaction may decrease if content deviates too much from preferences
Solution Approach 1:
The adventurousness parameter serves as a control variable that adjusts the degree of content deviation from baseline preferences. By changing this parameter, the system can smoothly transition between exploring diverse content (high adventurousness) and sticking to preferred content (low adventurousness), allowing users to balance discovery and satisfaction based on their current state.
Solution Approach 2:
The system implements dynamic control over content exploration by allowing users to adjust the adventurousness parameter in real-time. This dynamic approach enables users to increase content diversity when seeking discovery and decrease it when prioritizing satisfaction, creating a flexible balance between exploration and exploitation that adapts to immediate user needs.
3Reliability
If content selection always stays close to baseline preferences, then user satisfaction is maintained, but user engagement and discovery are limited
Solution Approach 1:
The adventurousness parameter enables users to control the degree of deviation from baseline preferences, allowing them to increase engagement by exploring diverse content while maintaining the option to return to safe, satisfying content. This parameter-based approach transforms content selection from a static satisfaction-optimization problem to a dynamic engagement-enhancing system.
Solution Approach 2:
The system enhances user engagement by implementing dynamic control over content exploration through the adventurousness parameter. Users can actively adjust their content discovery level to match their engagement needs, transforming passive content consumption into an interactive experience where users control their own engagement level with diverse content.
Data Source
AI summary
Systems and methods are provided for transmitting a next suggested item of content based on a current mood or emotion of a user. An item pool is accessed, where the item pool contains a plurality of items, and where each item is associated with a parameter. A baseline position is identified, where the baseline position is associated with a particular value of the parameter. A user-controllable parameter is received, where the user-controllable parameter indicates a user preference for a next item relative to the baseline position. The next item is selected based on the baseline position and the user-controllable parameter, and the next item is provided via a computer network.