Entity Resolution Microservice for Reducing Irrelevant Search Results

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Solution Overview

Problem

Existing search engine queries, such as those using ElasticSearch, often result in an overwhelming number of irrelevant search results, hindering real-time updates of entity profiles due to excessive data retrieval.

Innovation Solution

Implementing an entity resolution microservice that utilizes data-size-reducing hash functions to cluster and compress entity-specific data, followed by a scoring mechanism to generate targeted database queries, thereby reducing unnecessary search results.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If traditional search engine queries are used to retrieve entity-specific data, then comprehensive data retrieval is achieved, but the number of irrelevant search results becomes overwhelming

Engineering Contradiction:

Improvenumber of search resultsVSAvoidirrelevant search results

Core Design Contradiction:

Quantity of substanceVSLoss of information

Solution Approach 1:

The patent extracts only the necessary entity-specific features (such as name, address, phone number) from the complete entity data and uses these extracted features to construct targeted search queries. This extraction process filters out irrelevant information before the search phase, reducing the quantity of irrelevant results while maintaining comprehensive data retrieval capability.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent segments the entity data into distinct features (name, address, phone number, etc.) and uses each feature separately to construct search queries. This segmentation allows the system to retrieve data for each feature independently and then combine the results, thereby reducing the overall number of irrelevant results while maintaining comprehensive coverage.

Inventive Principle:

Principle #1Segmentation

2Loss of information

If comprehensive entity data is retrieved from databases, then complete entity information is obtained, but real-time update capability is hindered due to excessive data retrieval

Engineering Contradiction:

Improvecomplete entity informationVSAvoidreal-time update capability

Core Design Contradiction:

Loss of informationVSProductivity

Solution Approach 1:

The patent extracts only the essential entity features needed for updates (name, address, phone number) and constructs search queries based on these extracted features. This extraction enables the system to retrieve only the necessary data for real-time updates, maintaining complete entity information while significantly improving update speed by avoiding excessive data retrieval.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent performs preliminary actions by pre-processing entity data to extract and prepare the necessary features before update operations are needed. This preliminary extraction and preparation of entity features allows the system to quickly retrieve and process only the essential information during real-time updates, maintaining completeness while improving productivity.

Inventive Principle:

Principle #10Preliminary action

3Quantity of substance

If traditional database search queries are executed, then all entity data is retrieved, but data processing efficiency decreases due to processing excessive irrelevant data

Engineering Contradiction:

Improvedata retrieval volumeVSAvoiddata processing efficiency

Core Design Contradiction:

Quantity of substanceVSProductivity

Solution Approach 1:

The patent extracts only the necessary entity features (name, address, phone number) and uses these to construct targeted search queries. This extraction reduces the data retrieval volume to only what is needed, thereby improving data processing efficiency by eliminating the processing of excessive irrelevant data while maintaining complete entity information retrieval.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent segments the data processing task into separate operations: extracting entity features, constructing search queries, retrieving data, and processing results. This segmentation allows efficient processing of only the necessary data at each stage, improving overall data processing efficiency while maintaining comprehensive data retrieval capability.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20250291861A1Computer-based systems configured for generating search queries for a search engine and methods of use thereof

Publication Date: 2025.09.18 CAPITAL ONE SERVICES LLC

AI summary

A method may include executing an entity resolution microservice programmed to receive an entity-specific data request for entity-specific data for an entity from a plurality of entities. An application programming interface (API) call is transmitted to an entity profile database that programs the entity profile database to identify entity-specific data in data records matching the entity-specific data in the entity-specific data request and transmit to the entity resolution microservice a compressed representation of the entity-specific data identified in the at least one entity profile database. The compressed representation may be received and the compressed representation may be transformed to an uncompressed representation. An entity-specific database query request for a search engine to perform a database search for additional entity-specific data is generated based on the uncompressed representation.