AI Input Classification for Reusing User Data Across Services
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing computing systems require users to repeatedly input similar information for various Internet services, lacking an efficient method to simplify this process using AI technology.
Innovation Solution
An electronic device equipped with a text classification model using machine learning to identify and classify input information, allowing automatic input into relevant fields of a user interface, utilizing optical character recognition (OCR) and machine learning models to streamline information input across applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If users repeatedly input similar information for various Internet services, then information can be provided to multiple services, but user effort and time consumption increase
Solution Approach 1:
The system performs preliminary action by classifying and storing input information in a database during the first service interaction. This pre-processed information is then automatically retrieved and input into subsequent services, eliminating the need for users to repeatedly enter the same information and significantly reducing time consumption.
Solution Approach 2:
The system enables self-service by automatically retrieving stored information and inputting it into different service interfaces without requiring user intervention. The machine learning model autonomously determines which stored information to retrieve and how to format it for different services, making the system self-sufficient in handling information reuse across services.
2Measurement precision
If users manually input information for each service, then information can be accurately provided, but ease of operation decreases
Solution Approach 1:
The system incorporates feedback mechanisms where the machine learning model continuously learns from user interactions and service responses. This feedback loop allows the system to improve its information classification and retrieval accuracy over time, ensuring that automatically input information maintains high accuracy while increasingly improving ease of operation.
Solution Approach 2:
The system introduces an intermediary mechanism in the form of a machine learning-based information matching module. This intermediary automatically matches stored information with required service fields, serving as a mediator between the user's initial input and the multiple service interfaces, thereby maintaining accuracy while eliminating manual re-input requirements.
3Ease of operation
If a machine learning-based automatic input system is implemented, then ease of operation improves, but device complexity increases
Solution Approach 1:
The system applies universality by implementing a single machine learning-based information classification and retrieval mechanism that serves multiple services simultaneously. This multi-functional approach consolidates what would otherwise require separate information handling systems into one unified framework, improving ease of operation across all services while managing complexity through shared infrastructure.
Solution Approach 2:
The system uses copying by creating a standardized representation of user information in a centralized database structure. Instead of maintaining separate information storage mechanisms for each service, the system creates a universal information copy that can be retrieved and adapted for different service interfaces, simplifying the overall system architecture while enabling automatic information input across multiple services.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Provided are a method and apparatus for classifying and storing input information based on machine learning and artificial intelligence and automatically inputting the stored information. According to an exemplary embodiment, input information is classified and stored using machine learning, an input item to which the stored input information is to be input is identified using machine learning, and the stored input information is input to the input item.