Context-Aware Information Circuits for Unified Notification Curation
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Solution Overview
Problem
Current systems fail to efficiently manage and curate the vast amount of data generated daily, as users are inundated with disjointed notifications and alerts, lacking a unified solution to contextualize and relate information relevant to their interests, behaviors, and geographical location.
Innovation Solution
A DI-based computerized framework that leverages AI and LLMs to build, curate, and manage circuits of information tailored to user contexts, integrating data from disparate sources and providing a unified network location for timely information consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users manually sift through notifications and alerts via individual applications, then they can access information, but they cannot keep up with the constant stream of information and lack context about how notifications relate to each other and to the user
Solution Approach 1:
The patent combines multiple disparate notifications and alerts from different applications into a single unified dashboard interface. This consolidation allows users to view all information in one location rather than switching between applications, thereby preventing information loss and reducing the time required to process notifications.
Solution Approach 2:
The system introduces an intermediary processing layer that automatically analyzes, contextualizes, and organizes notifications before presenting them to users. This intermediary component adds contextual information about how notifications relate to each other and to user profiles, eliminating the need for manual information synthesis.
2Adaptability or versatility
If current AI search engines scan and index data to personalize results, then they can provide personalized information, but they are tied to siloed data storage and cannot identify information from disparate network locations
Solution Approach 1:
The system implements a universal data collection mechanism that can access and integrate information from multiple disparate sources including social media platforms, news websites, weather services, and local business databases. This multi-functional capability allows the system to gather comprehensive information from across the web rather than being limited to siloed data storage.
Solution Approach 2:
The patent extends the data collection capability from local or single-source storage to a multi-dimensional network architecture that accesses information across different network locations and platforms. This dimensional expansion enables the system to retrieve information from diverse sources and compile them into a comprehensive unified view.
3Loss of information
If the system compiles customized circuits with information from multiple sources, then it provides comprehensive and contextually relevant information, but it requires complex data processing and integration mechanisms
Solution Approach 1:
The system segments the complex data processing task into distinct functional modules: data collection from various sources, data cleaning and validation, contextual analysis, circuit compilation, and dashboard presentation. This modular segmentation manages complexity by organizing the processing pipeline into manageable, independent components that can be developed and maintained separately.
Solution Approach 2:
The system implements automated self-service mechanisms that perform data collection, validation, and circuit compilation without requiring manual intervention. The automated processes continuously monitor data sources, retrieve relevant information, and update user dashboards autonomously, reducing the operational complexity while maintaining high information relevance.
Data Source
AI summary
Disclosed are systems and methods for a decision intelligence (DI)-based computerized framework that provides customized circuits that enable interactions for users with curated, network-hosted electronic resources, as they relate to a user(s). The disclosed framework provides mechanisms for determining and leveraging a deep user-based context to automatically surface information and/or recommend actions that are temporally, spatially, socially and/or logically relevant to a user. The framework operates to build, curate and manage a circuit on/over a network at a network location via the retrieval and AI/ML and/or LLM-based analysis of data, which can enable enhanced consumption, and improved interactions on/over the network, with other network resources and/or other users.