Image Mining Platform for Risk Applications
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Analyzing large amounts of image data for risk-related applications is challenging due to the difficulty in identifying patterns across diverse data sets and the time-consuming, error-prone process of managing different business logic requirements across various applications.
Innovation Solution
A system and method for efficiently and accurately mining image data by receiving input from multiple sources, aggregating and mapping the data, automatically detecting events triggered by rules and tags, updating a database with detected events and rules, and transmitting indications to risk applications, utilizing an image mining platform with a computer processor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual management of different business logic rules for multiple applications is used, then flexibility in handling different application requirements is maintained, but time consumption and error rate increase significantly
Solution Approach 1:
The patent merges multiple application-specific business logic rules into a single centralized image mining platform. The platform consolidates data aggregation, event detection, and analysis functions that previously were manually managed separately for each application, thereby reducing time consumption and errors while maintaining the ability to handle different application requirements through a unified system.
Solution Approach 2:
The image mining platform is designed as a universal system that can serve multiple risk-related applications simultaneously. It implements multi-functional capabilities to handle different types of image data, apply various business logic rules, and support diverse analysis requirements across insurance, finance, and other risk assessment domains without requiring separate manual management for each application.
2Productivity
If automated event detection is implemented, then analysis speed and consistency improve, but system complexity increases
Solution Approach 1:
The patent segments the image mining platform into distinct functional modules: data aggregation module, event detection module, rule evaluation module, and result generation module. Each module performs a specific function in the automated analysis pipeline, which improves processing speed and consistency while managing system complexity through modular design that allows independent development and maintenance of each component.
3Loss of information
If comprehensive image data from multiple sources is aggregated, then analysis completeness and pattern recognition improve, but data processing complexity and time increase
Solution Approach 1:
The patent introduces an intermediary data aggregation and mapping layer between multiple image data sources and the event detection engine. This intermediary layer standardizes data from diverse sources into a unified format, enabling comprehensive pattern recognition across multiple applications while simplifying the complexity of handling heterogeneous data through a standardized intermediate representation.
Data Source
AI summary
In some embodiments, image input data is received from multiple sources. The received image input data may then be aggregated and mapped to create a set of image input data. An event in the set of image input data may be automatically detected, such as by being triggered by a rule and an associated tag. An image mining result database may be updated by adding an entry to the database identifying each detected event and the triggering rule. An indication associated with the image mining result database may then be transmitted to a plurality of risk applications.