Statistical Model Vector Matching for Creative Professionals

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Solution Overview

Problem

Current systems for matching photographers to projects are laborious and subjective, leading to inconsistent results and underutilization of available photographers, as they rely on manual human review and are not optimized for non-tangible creative professionals.

Innovation Solution

A computer-implemented method using a statistical model to determine vector representations of creative professionals based on project criteria and profile information, calculating distances to provide automated recommendations for project assignments.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual human review is used to match photographers to projects, then subjective expertise can be applied, but the process becomes laborious and time-consuming

Engineering Contradiction:

Improvematching accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical review process with an automated computer-based system that uses machine learning models and algorithms to match photographers with projects, eliminating the need for human reviewers while maintaining or improving matching quality

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables automatic self-matching where the computer-based algorithm independently evaluates photographer profiles against project requirements and generates matches without human intervention, making the system self-sufficient in the matching task

Inventive Principle:

Principle #25Self-service

2Manufacturing precision

If manual review processes are used, then detailed evaluation can be performed, but scalability is limited and resources are heavily burdened

Engineering Contradiction:

Improveevaluation qualityVSAvoidsystem scalability

Core Design Contradiction:

Manufacturing precisionVSProductivity

Solution Approach 1:

The patent substitutes manual evaluation processes with automated computer-based analysis that can process numerous photographer profiles simultaneously, enabling high-quality evaluation at scale without additional human resources

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The computer-based system is designed to handle multiple functions including profile analysis, project requirement parsing, matching algorithm execution, and recommendation generation, making it a universal platform that can serve diverse matching needs

Inventive Principle:

Principle #6Universality (Multi-functionality)

3Adaptability or versatility

If subjective matching approaches are used, then human judgment can be applied, but inconsistent results and biases occur

Engineering Contradiction:

Improvematching flexibilityVSAvoidmatching consistency

Core Design Contradiction:

Adaptability or versatilityVSReliability

Solution Approach 1:

The patent transforms subjective matching criteria into objective quantifiable parameters that can be processed by algorithms, converting flexible human judgment into consistent measurable metrics that maintain adaptability while ensuring reliability

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The system incorporates feedback mechanisms where matching results are continuously evaluated and used to refine the algorithm, ensuring consistent application of criteria while adapting to improve performance based on outcomes

Inventive Principle:

Principle #23Feedback

4Productivity

If automated systems are implemented, then processing speed improves, but handling non-tangible creative professionals becomes challenging

Engineering Contradiction:

Improveprocessing speedVSAvoidevaluation complexity

Core Design Contradiction:

ProductivityVSDifficulty of detecting and measuring

Solution Approach 1:

The patent introduces intermediary elements such as structured profile data, standardized metadata, and algorithmic mediators that translate intangible creative professional attributes into measurable forms that can be processed automatically at high speed

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11276008B1Providing recommendations of creative professionals using a statistical model

Publication Date: 2022.03.15 SHUTTERSTOCK

AI summary

A method for providing recommendations of creative professionals to complete a project is provided. The method includes receiving information related to a project, the information including a first set of criteria associated with the project. The method includes determining, using a statistical model, a vector representation corresponding to a candidate creative professional based on the information related to the project. The method also includes determining respective vector representations of a first set of creative professionals based at least in part on profile information related to each of the creative professionals. The method includes determining respective distances of each of the respective vector representations from the vector representation corresponding to the candidate creative professional. Further, the method includes providing a second set of creative professionals as recommendations for being assigned to the project based at least in part on the respective distances.