Adaptive Content Selection with User-Controlled Adventurousness
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Solution Overview
Problem
Existing content distribution systems 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 content items from a pool based on a baseline position, allowing users to adjust their preference for deviation from the baseline.
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 patent implements dynamic content selection by allowing users to adjust the adventurousness parameter in real-time, enabling the system to adapt to changing preferences without requiring complex reconfiguration. The baseline position and adventurousness parameter work together to dynamically select content that matches current user mood while maintaining system simplicity.
Solution Approach 2:
The system uses parameter changes by introducing the adventurousness parameter that modifies content selection based on user preference intensity. By varying this parameter, the system can adapt to different user states without changing the underlying system architecture, thus improving adaptability while controlling complexity.
2Adaptability or versatility
If content selection always deviates from baseline to provide variety, then user engagement increases, but it may provide content that does not match user tastes
Solution Approach 1:
The patent applies local quality by allowing different degrees of deviation from the baseline position based on the adventurousness parameter. When adventurousness is low, content stays close to baseline ensuring relevance; when high, content deviates more to provide variety. This localized adjustment of deviation quality maintains both reliability and adaptability.
Solution Approach 2:
The system uses partial action by selecting content that partially deviates from the baseline position rather than always maximizing deviation. The adventurousness parameter controls the degree of deviation, allowing the system to provide just enough variety to maintain engagement while staying within acceptable relevance bounds.
3Reliability
If content selection closely follows baseline position, then content relevance is high, but user engagement may decrease due to lack of variety
Solution Approach 1:
The system dynamically adjusts the balance between baseline adherence and deviation based on user-controlled adventurousness. This dynamic approach allows the system to maintain high relevance when users prefer familiar content while occasionally introducing variety to sustain engagement, thus improving productivity without sacrificing reliability.
4Ease of operation
If the system automatically adjusts content based on inferred preferences, then ease of operation is high, but loss of information about true user intent increases
Solution Approach 1:
The patent implements self-service by enabling users to directly control the adventurousness parameter themselves rather than relying on system inference. This allows users to maintain ease of operation through simple parameter adjustment while preserving accurate information about their true intent, as they explicitly state their preference for deviation from baseline.
Data Source
AI summary
Systems and methods are provided for operating a user-controllable parameter. 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.