Searchable Query Graphs for Dynamic Entity Correlation Analysis

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Solution Overview

Problem

Conventional methods for analyzing and presenting data are limited by high costs, reliance on manpower, and become obsolete over time, lacking scalability and unbiased insights into complex entities and concepts.

Innovation Solution

A query graph generation system that analyzes digital content items to identify entities and concepts, generating a searchable graph object with correlations, providing an unbiased and scalable representation that updates over time.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If conventional techniques for analyzing and presenting data are used, then data collection and analysis can be performed, but significant costs and time are incurred due to reliance on focus groups, surveys, and large quantities of manpower

Engineering Contradiction:

Improvedata analysis efficiencyVSAvoidtime required for data collection and analysis

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The patent replaces manual mechanical analysis methods (focus groups, surveys, human observation) with an automated computer-based system that uses algorithms to analyze digital content items. The system automatically identifies entities, extracts concepts, generates graphs, and presents insights without requiring human manpower for data collection and analysis, thereby dramatically improving productivity while reducing time consumption.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If conventional data analysis methods are used, then insights can be obtained, but the analysis becomes obsolete over time and lacks adaptability to changing data

Engineering Contradiction:

Improveadaptability to changing dataVSAvoidrelevance period of analysis results

Core Design Contradiction:

Adaptability or versatilityVSDuration of action of stationary object

Solution Approach 1:

The patent implements a dynamic system that continuously updates its analysis by receiving new digital content items and regenerating graphs based on current data. The system adapts to changing data by automatically identifying new entities and concepts, updating entity-concept relationships, and presenting refreshed insights. This dynamic approach ensures the analysis remains relevant and adaptable rather than becoming obsolete over time.

Inventive Principle:

Principle #15Dynamics

3Loss of information

If comprehensive data analysis is performed on all digital content items, then complete insights are obtained, but the complexity and computational resources required increase significantly

Engineering Contradiction:

Improvecompleteness of insightsVSAvoidsystem complexity

Core Design Contradiction:

Loss of informationVSDevice complexity

Solution Approach 1:

The patent segments the analysis process into distinct modular components: receiving digital content items, identifying entities within those items, extracting concepts associated with entities, generating graphs representing entity-concept relationships, and presenting insights. This segmentation allows the system to process comprehensive data through manageable stages, reducing overall system complexity while maintaining complete insights at each processing level.

Inventive Principle:

Principle #1Segmentation

4Measurement precision

If manual observation and analysis of content is performed, then meaningful insights can be gained, but large quantities of manpower are required increasing costs

Engineering Contradiction:

Improvequality of insightsVSAvoidautomation level

Core Design Contradiction:

Measurement precisionVSExtent of automation

Solution Approach 1:

The patent replaces manual observation and analysis with automated computer-based processing that systematically identifies entities, extracts concepts, and generates insights from digital content. The automated system maintains measurement precision by using consistent algorithmic methods to analyze all content items, eliminating human subjectivity while preserving the quality of insights through structured data processing and relationship mapping.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12481673B2Generating and presenting a searchable graph based on a graph query

Publication Date: 2025.11.25 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

The present disclosure relates to selectively analyzing digital content items from a social networking system to generate a searchable graph object that facilitates visualization of correlations between entities of interest (e.g., brands, products, services, companies), concepts (e.g., domain-specific and/or general terms), hashtags, and other output classes. For example, systems described herein involve collecting images and/or videos that are publicly available via a social networking platform and evaluating content and metadata thereof to identify entities of interest therein and predict various concepts therein to generate a graph object that provides a searchable matrix. The systems herein provide a mechanism for processing a graph query that presents a relational graph showing correlations between the query and the various output classes.