Entity Information Verification Using Candidate Entity Sets
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Solution Overview
Problem
Existing methods for verifying entity information, such as location and real scene images, rely on human review, which is subjective, inaccurate, and limited by time and manpower, making it difficult to ensure timeliness and authenticity.
Innovation Solution
A method and apparatus that determine a candidate entity set based on location information, using proximity or non-proximity conditions, allowing users to verify entity information objectively, reducing the need for human intervention and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human review is used to verify entity information, then verification can be performed subjectively based on experience, but verification accuracy is very low due to complexity and variability of location information and real scene images
Solution Approach 1:
The patent replaces the mechanical human review system with an automated image recognition system. The system automatically extracts location information and real scene images from entity information, uses image recognition technology to verify authenticity, and compares extracted information with database records, thereby eliminating subjective human judgment and achieving objective, high-accuracy verification
Solution Approach 2:
The patent introduces an intermediary image recognition system between the entity information and the verification result. This intermediary automatically processes location information and real scene images, extracts key features, matches them with database records, and provides objective verification conclusions, serving as a mediator that bridges the gap between raw entity data and verification outcomes
2Ease of operation
If human review is used to verify entity information, then verification can be performed manually, but verification timeliness cannot be continuously guaranteed due to working hours and manpower limitations
Solution Approach 1:
The patent implements self-service verification where the system automatically verifies entity information without requiring human intervention. The image recognition system independently extracts location information and real scene images, compares them with database records, and returns verification results continuously and automatically, eliminating human working hour constraints and achieving continuous verification timeliness
Solution Approach 2:
The patent ensures continuous verification by implementing an automated system that operates without interruption. The image recognition system continuously processes entity information, extracts features, matches with database records, and returns results 24/7 without the limitations of human working hours, thereby guaranteeing continuous verification timeliness
3Ease of operation
If human review is used to verify location information and real scene images, then verification can be performed based on experience, but forgery of location information and real scene images is very simple, causing great interference to human review
Solution Approach 1:
The patent replaces subjective human review with objective automated image recognition. The system uses machine learning models and feature extraction algorithms to automatically detect patterns, landmarks, and characteristics in real scene images and location information, comparing them against verified database records. This automated approach is not susceptible to forgery interference since it relies on algorithmic pattern recognition rather than human experience-based judgment
Solution Approach 2:
The patent implements a feedback mechanism where the image recognition system continuously compares extracted information with verified database records and returns objective verification results. The system receives feedback from the database verification process and automatically adjusts its recognition parameters, providing continuous objective verification that is resistant to forgery attempts
Data Source
AI summary
This specification describes techniques for verifying location information. One example method includes identifying location information associated with a particular entity; determining, based on the location information, a candidate entity set including a plurality of candidate entities, wherein each candidate entity is different than the particular entity, and wherein the candidate entity set includes a correct set including candidate entities that satisfy candidate location criteria; sending the candidate entity set and the candidate location criteria to the particular entity; receiving a selected entity set including one or more of the candidate entities; determining that the selected entity set includes a number of candidate entities from the correct set satisfies a location verification threshold; and in response determining that the selected entity set includes the number of candidate entities from the correct set that exceeds the location verification threshold, determining that the location information of the particular entity is verified.