Server Overlay System for Cross-Platform Text Extraction and Action Suggestions
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users face challenges in efficiently sorting and prioritizing increasing amounts of information, leading to reduced productivity due to the lack of suitable methods for automating repetitive tasks and identifying relevant information across multiple applications and devices.
Innovation Solution
A server-based system that extracts text from shared applications, associates it with user actions, and generates overlays to suggest actions, using a concept map to weight importance and automate repetitive tasks across multiple client devices, regardless of platform or network.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually sort and prioritize information across multiple applications and devices, then they can identify relevant information, but productivity decreases due to time-consuming manual sorting
Solution Approach 1:
The system automatically extracts text from applications and performs sorting and prioritization without requiring user intervention. The server autonomously monitors applications, extracts relevant text using OCR or other extraction methods, weights the extracted text based on predefined criteria, and generates suggestions, enabling the system to serve itself rather than requiring manual user processing of information across multiple applications.
Solution Approach 2:
The system performs text extraction, weighting, and suggestion generation in advance before users need to sort information manually. By continuously monitoring applications and pre-processing text content, the system prepares sorted and prioritized information suggestions that are ready when users need them, eliminating the need for real-time manual sorting during information review.
2Productivity
If the system extracts and processes text from multiple shared applications across diverse platforms, then information triage efficiency improves, but system complexity increases
Solution Approach 1:
The server acts as an intermediary between diverse client devices and applications, centralizing the text extraction and processing functionality. Rather than implementing complex extraction logic in each client device or application, the server mediates the process by receiving data from various sources, performing uniform text extraction and weighting operations, and returning processed results, thereby simplifying the overall system architecture while maintaining cross-platform compatibility.
Solution Approach 2:
The server implements a universal text extraction and weighting system that handles multiple application types and platforms through a single centralized service. The system uses application-agnostic methods such as OCR and screen capture to extract text from diverse sources including Windows applications, macOS applications, and web browsers, providing multi-functional text processing capability through a unified architecture that reduces overall system complexity.
3Extent of automation
If the system provides automated action suggestions through overlays, then repetitive task automation improves, but user interaction complexity increases
Solution Approach 1:
The system provides partial automation by generating action suggestions that require minimal user confirmation rather than complete automation. The overlay presents suggested actions to the user, who can approve or modify them with a single click, implementing partial automation that handles the complex text processing and suggestion generation while keeping the final decision in user hands, thereby maintaining ease of operation while achieving significant automation of repetitive task analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system enhances user productivity by automating repetitive tasks and highlighting relevant information, improving information triage efficiency and reducing the time spent on sorting through large volumes of data across diverse applications and devices.
Implementation Method 1
The processor may also be configured to perform optical character recognition (OCR) to extract text displayed by at least one of the shared applications on the display
Data Source
AI summary
A server may include a memory and a processor configured to cooperate with the memory to provide access to shared applications by a client computing device, extract text displayed by the shared applications on the display while the shared applications are being used by the client computing device, associate the extracted text with actions initiated by the client computing device in a relational database after displaying respective text on the display, and weight the extracted text within the relational database. The processor may further determine a suggested action to perform based upon text subsequently displayed on the display and the relational database, generate an overlay to be displayed on the display including the suggested action, and change a weighting associated with the extracted text in the relational database based upon a response to the suggested action included in the overlay by the at least one client computing device.