Interactive Data Modeling Platform Integrating Community Strategies
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Solution Overview
Problem
Current systems lack the infrastructure to integrate strategic planning modeling with community interaction functionality, unable to leverage community knowledge and interaction data for dynamic user-personalized strategies, provide simultaneous access to disparate systems, and execute multi-party communications within a single platform.
Innovation Solution
An interactive data modeling and communication platform that uses machine learning to generate user-personalized strategies, integrates with external data systems, and provides access to community data and tools, dynamically updating based on user interactions and data changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing systems use multiple separate platforms for strategic planning and community interaction, then system simplicity is maintained, but integration capability and ability to leverage community knowledge for personalized strategies deteriorates
Solution Approach 1:
The patent combines strategic planning modeling functionality with community interaction functionality into a single integrated platform. The system merges previously separate systems (strategic planning tools and community networks) into one unified platform that can simultaneously perform both functions and leverage their synergies.
Solution Approach 2:
The platform is designed to perform multiple functions: it provides strategic planning capabilities, community interaction features, data analytics, and personalized strategy generation all within a single system. This multi-functional design allows the system to serve diverse needs without requiring multiple separate platforms.
2Loss of information
If existing systems access data from disparate sources, then data availability is limited to individual systems, but system complexity and integration requirements deteriorates
Solution Approach 1:
The patent introduces an intermediary layer (the integrated platform) that connects to multiple external data sources including community networks, strategic planning systems, and external APIs. This intermediary consolidates access to diverse data sources, making information from disparate systems available through a single interface without requiring direct integration between all source systems.
3Adaptability or versatility
If systems provide static strategies, then implementation simplicity is maintained, but adaptability to changing user needs and community knowledge deteriorates
Solution Approach 1:
The patent implements dynamic strategies that automatically adapt based on changing conditions. The system continuously monitors user progress, community interactions, and external data sources, then dynamically updates and adjusts strategic recommendations. This allows strategies to evolve over time rather than remaining static, maintaining relevance and effectiveness.
Solution Approach 2:
The system incorporates feedback loops where user actions, community interactions, and outcome data are continuously fed back into the strategic modeling process. This feedback mechanism enables the system to learn from user behavior and community knowledge, refining and personalizing strategies based on real-world results and emerging patterns.
Data Source
AI summary
A novel system, method and computer program product are disclosed herein. The system may an interactive data modeling and communication platform (the “platform”) in communication with one or more user devices and external data systems. The platform may include one or more servers executing computer-readable instructions that cause the platform to perform operations such as generating and training machine learning models, receiving data and information relating to a plurality of users, converting the data and information into a suitable format for use by the machine learning models, and executing the machine learning models using the converted data and information as input. The machine learning models may generate user-personalized strategies and identify tools and resources for completing aspects of the user-personalized strategies. The operations may also include generating an interactive graphical user interface (GUI) that displays the user-personalized strategies and the tools and resources for completing aspects of the user-personalized strategies.