Multi-Space Data Projections for Personalized Schedule Planning
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Solution Overview
Problem
Users face challenges in managing their finite schedules to effectively participate in activities that boost performance across multiple life domains, requiring an optimal schedule that balances priorities and conflicts.
Innovation Solution
A method and apparatus that utilize a computing device to generate projections of user data representations in multiple spaces, incorporating dynamic weightings and large language models to create personalized schedules and notifications, allowing users to track progress and achieve domain-specific targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a user manually manages their schedule to balance multiple life domains, then they can maintain control over their time, but they cannot effectively participate in activities that boost performance across all domains due to time constraints
Solution Approach 1:
The system automatically generates optimal schedules and projections without requiring manual intervention from the user. The computing device autonomously processes user data, applies dynamic weightings, generates representations in multiple spaces, and creates optimized schedules that balance multiple life domains, allowing the system to serve itself rather than requiring continuous user management
Solution Approach 2:
The system performs preliminary analysis by generating representations of user data in multiple spaces before creating the optimal schedule. By pre-processing user data, calculating dynamic weightings, and projecting representations across different dimensional spaces, the system prepares all necessary information in advance to quickly generate an optimized schedule that maximizes performance across domains
2Measurement precision
If the system generates detailed projections in multiple spaces with dynamic weightings, then goal clarity and schedule optimization improve, but computational complexity increases
Solution Approach 1:
The system transforms user data into representations across multiple dimensional spaces, where each space captures different aspects of the data with specific weightings. By projecting data into second, third, and higher dimensional spaces, the system achieves more precise goal clarity and schedule optimization by analyzing relationships from multiple perspectives simultaneously, rather than being constrained to a single dimensional view
Data Source
AI summary
Aspects of the present disclosure generally relate to apparatus and method of generating projections of representations of data in a plurality of spaces.