Context-Aware Smartphone App Selection and Reward Token System
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Solution Overview
Problem
Existing technologies fail to effectively curate and contextually select the most relevant applications on mobile devices for users, and lack integrated techniques for rewarding users based on their usage or non-usage of applications in a holistic manner, especially not awarding rewards as cryptocurrency tokens.
Innovation Solution
The system employs context-aware techniques to select and rank-order smartphone applications based on user and application contexts, using a comparison engine to determine similarity between user and application context vectors, and awards reward points in a digital wallet that can be redeemed as cryptocurrency tokens.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If applications are curated and selected based on user context and application context similarity, then application relevance and personalization are improved, but system complexity increases due to context vector processing and comparison engine requirements
Solution Approach 1:
The patent introduces a comparison engine as an intermediary component that processes context vectors and determines similarity between user context and application context. This mediator handles the complex computations, isolating the complexity from the core application selection logic and making the system more manageable while maintaining high adaptability.
Solution Approach 2:
The patent transforms the application selection problem into a parameter-based similarity calculation problem. By representing both user context and application context as vectors with specific parameters, the system can use mathematical similarity metrics to objectively determine relevance, improving adaptability while systematic parameter processing manages complexity.
2Productivity
If reward points are awarded based on holistic user behavior analysis, then user engagement is improved, but computational requirements and processing time increase
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing context vectors for applications and maintaining user context profiles in advance. When reward determination is needed, the system compares against pre-prepared data structures, significantly reducing real-time processing requirements while still enabling holistic behavior analysis for improved user engagement.
3Measurement precision
If context vectors are continuously updated and compared to determine application similarity, then personalization accuracy is improved, but energy consumption increases
Solution Approach 1:
The patent implements periodic action by updating context vectors and performing similarity comparisons at specific intervals or triggered by significant user events, rather than continuously. This approach maintains personalization accuracy by keeping context data current while dramatically reducing energy consumption by avoiding constant computational operations.
Data Source
AI summary
Systems and methods are disclosed for providing context-aware selection and recommendation of applications and services on a mobile device. The selection of the preferred applications is based on the context of the user and the context of the applications. A comparison engine related to a recommendation module performs a similarity computation between context attribute vectors of the user and the applications. Based on the similarity computation, a rank-order is produced that determines in what order the application icons should be presented to the user. A digital wallet is also disclosed that maintains the reward points awarded to the user as crypto/virtual tokens based on the instant principles. Unlike prevailing techniques, the reward points are awarded in a context-aware manner after reconciling the conflicting or contradictory usage habits of the user.