Universal Entity Identification Indexing for Inconsistent Data Sources
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Solution Overview
Problem
Existing systems face challenges in amalgamating entity data from disparate databases due to the lack of a common identification system, leading to inconsistent data retrieval and potential confusion between entities, which can result in incorrect decisions.
Innovation Solution
A system that includes an indexing system generating universal identifiers for entities across multiple databases, using a two-step process to match database identifiers based on various criteria and scoring to solidify matches, with an API for accessing and querying these identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is retrieved from multiple unrelated databases using their unique identification systems, then comprehensive entity data can be collected, but data inconsistency and entity confusion occur due to lack of common identification
Solution Approach 1:
The patent introduces an intermediary entity identification system that acts as a mediator between multiple unrelated databases. This system receives entity data from various databases with different identification systems, reconciles them through matching algorithms, and outputs unified entity data with consistent identification. The intermediary layer resolves the contradiction by enabling comprehensive data collection while ensuring data consistency through its reconciliation function.
2Adaptability or versatility
If multiple database identification systems are used to access different databases, then access to diverse entity data is enabled, but the complexity of the identification and matching process increases
Solution Approach 1:
The patent implements a universal entity identification system that can handle multiple database identification systems through a single unified interface. This universal system performs multiple functions: it accepts various identification formats from different databases, applies matching algorithms, and outputs standardized entity data. By consolidating multiple identification functions into one universal system, the patent enables access to diverse databases while managing complexity through standardization.
3Measurement precision
If entity matching is performed across databases with different identification systems, then accurate entity identification can be achieved, but the time and computational resources required increase
Solution Approach 1:
The patent applies preliminary action by pre-processing entity data from multiple databases before the actual matching process. This includes standardizing data formats, pre-computing identification features, and organizing data structures in advance. By performing these preparatory actions beforehand, the system reduces the computational burden during the actual entity matching process, thereby maintaining high identification accuracy while reducing the time and resources required for data retrieval and matching operations.
Data Source
AI summary
A system for accessing and amalgamating entity data from a plurality of inconsistent data sources may be provided. The system may include a plurality of databases. The plurality of databases may include a first database and a second database. The first database may include a first plurality of entity datasets. Each entity dataset of the first plurality of entity datasets may relate to an entity. The first database may include a first database identifier for each entity dataset. The second database may include a second plurality of entity datasets. Each entity dataset of the second plurality of entity datasets may relate to an entity. The second database may include a second database identifier for each entity dataset. One entity dataset included in the first database may relate to the same entity as an entity dataset included in the second database. The system may include an indexing system.