Multi-value Primary Keys for Database Duplicate Detection

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Solution Overview

Problem

Current database systems face challenges in seamlessly and effortlessly managing duplicate data entries across multiple systems, particularly in enterprise and technical applications, where entries representing the same physical entity are often duplicated with slight variations, making it difficult to aggregate data and apply functionalities like customer discounts.

Innovation Solution

A computer-implemented method and database system that uses a multi-valued key and prioritized naming rules to determine hash values for attribute combinations, allowing for the unambiguous identification and merging of duplicate data items, thereby maintaining primary key uniqueness and facilitating efficient data management.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional database systems store duplicate customer records with slight variations, then data can be entered flexibly, but data integrity and uniqueness are compromised

Engineering Contradiction:

Improvedata entry flexibilityVSAvoiddata uniqueness

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The system performs preliminary actions by establishing naming rules and prioritization criteria before duplicate data enters the database. When data is inserted, the system proactively checks for duplicates by comparing against existing records using the predefined naming rules, preventing duplicate entries before they compromise data integrity.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary mechanism (duplicate detection system with naming rules) that mediates between flexible data entry and data uniqueness requirements. This intermediary layer processes incoming data, compares it with existing records using prioritized naming rules, and determines whether to accept or reject the entry, thus resolving the contradiction between flexibility and uniqueness.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Ease of operation

If duplicate data entries are allowed in the database, then data entry is simpler, but data aggregation and analysis become difficult

Engineering Contradiction:

Improvedata entry simplicityVSAvoiddata aggregation efficiency

Core Design Contradiction:

Ease of operationVSProductivity

Solution Approach 1:

The system performs preliminary duplicate detection and prevention before data aggregation operations are needed. By establishing naming rules and checking for duplicates at data insertion time, the system ensures data quality upfront, eliminating the need for complex post-hoc aggregation workarounds and improving downstream productivity.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system implements feedback mechanisms where duplicate detection results inform data entry operations. When a potential duplicate is detected, the system provides feedback about the match and allows for resolution, ensuring that only unique, high-quality data enters the database, thereby maintaining aggregation efficiency.

Inventive Principle:

Principle #23Feedback

3Reliability

If manual merging of duplicate records is performed, then data accuracy can be maintained, but time consumption and operational complexity increase

Engineering Contradiction:

Improvedata accuracyVSAvoidmerging time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs self-service by automatically detecting and preventing duplicate data entries using predefined naming rules and prioritization criteria. This automated approach maintains data accuracy without requiring manual intervention, eliminating the time loss associated with manual merging operations while preserving reliability through systematic duplicate prevention.

Inventive Principle:

Principle #25Self-service

4Quantity of substance

If multiple naming variations of the same entity are stored, then data collection is more comprehensive, but system complexity and maintenance difficulty increase

Engineering Contradiction:

Improvedata completenessVSAvoidsystem maintenance complexity

Core Design Contradiction:

Quantity of substanceVSDevice complexity

Solution Approach 1:

The system changes the parameter of data representation by standardizing entity identification through prioritized naming rules. Instead of storing multiple naming variations as separate records, the system transforms diverse input formats into a standardized representation, maintaining data completeness while reducing system complexity by eliminating redundant variations.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11604776B2Multi-value primary keys for plurality of unique identifiers of entities

Publication Date: 2023.03.14 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer-implemented method for unambiguously identifying entities in a database system may be provided. The method comprises storing data items as records with different attributes in a table of a database, storing naming rules for selected combinations of the attributes of the data items, and prioritizing the naming rules. The method also comprises determining a hash value for each of the selected combinations of the attributes of the data items, and identifying duplicate data items using the determined hash values and the prioritized naming rules.