Database Record Verification via Automated Pattern Matching

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Solution Overview

Problem

Maintaining the accuracy and up-to-dateness of large databases, such as those containing point of interest addresses, is challenging due to the volume of records and frequent changes, making manual maintenance inefficient and costly.

Innovation Solution

A system that uses pattern extraction, pattern recognition, and partial pattern matching to verify and update database records by crawling data from sources like websites and user-submitted content, utilizing machine learning to determine the accuracy of record items and assign weights to sources for reliability.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual maintenance of database records is used, then data accuracy can be maintained, but the process becomes expensive, inefficient, and time-consuming

Engineering Contradiction:

Improvedata accuracyVSAvoidmaintenance efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system enables self-service data verification and correction by automatically crawling data from external sources, comparing it with existing database records, and identifying discrepancies without human intervention. The system serves itself by autonomously detecting outdated information and generating correction recommendations.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Manual mechanical processes of data verification and correction are replaced with automated electronic systems that use web crawling, pattern recognition, and machine learning algorithms to detect and correct data inaccuracies, eliminating the need for manual review and updating of database records.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If manual maintenance of database records is used, then data accuracy can be maintained, but costs increase significantly

Engineering Contradiction:

Improvedata accuracyVSAvoidmaintenance cost

Core Design Contradiction:

Measurement precisionVSLoss of energy

Solution Approach 1:

The system performs self-verification by automatically crawling external data sources and comparing them with stored records, eliminating the need for expensive manual verification services. The automated system identifies discrepancies and generates correction recommendations without human labor costs.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

Expensive manual data maintenance operations are replaced with cost-effective automated electronic processes that use web crawling and pattern recognition algorithms to verify and correct data accuracy, significantly reducing operational costs while maintaining high accuracy standards.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Quantity of substance

If databases continue to grow with new records, then data coverage improves, but maintaining accuracy becomes more challenging

Engineering Contradiction:

Improvedatabase volumeVSAvoiddata accuracy

Core Design Contradiction:

Quantity of substanceVSMeasurement precision

Solution Approach 1:

The system performs preliminary verification by crawling external data sources and comparing them with existing database records before finalizing data storage. This preliminary check ensures that new records meet accuracy standards before being added to the database, preventing propagation of inaccuracies.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system establishes a feedback loop where crawled data from external sources is continuously compared with existing database records, identifying discrepancies and generating correction recommendations. This feedback mechanism ensures that as the database grows, accuracy is maintained through systematic verification and correction processes.

Inventive Principle:

Principle #23Feedback

4Reliability

If record information is frequently updated to remain current, then data relevance improves, but the complexity of monitoring and verification increases

Engineering Contradiction:

Improvedata currencyVSAvoidmonitoring complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs multiple functions through a single unified process: crawling external data sources, comparing with existing records, identifying discrepancies, and generating correction recommendations. This multi-functional approach simplifies the monitoring process by consolidating various verification tasks into one automated system rather than requiring separate processes for each function.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10073870B2Method and apparatus for providing data correction and management

Publication Date: 2018.09.11 HERE GLOBAL BV

AI summary

An approach is provided for determining at least one entity specified in at least one data record. The approach further involves determining one or more data sources available from the at least one entity. The approach further involves processing and/or facilitating a processing of the one or more data sources to determine information for a verification, an update, or a combination thereof of the at least one data record.