Emotion Recognition Candidate Matching With Normalized Assessments
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Solution Overview
Problem
Traditional methods of matching job seekers with employers face challenges due to non-standardized assessments producing dissimilar results and suitability data in different formats, leading to difficulty in identifying the best candidates among a large pool of applicants.
Innovation Solution
A method that normalizes assessment data and suitability data to derive performance and position quotients, using facial diagnostics and social media analysis to match job seekers with employer preferences, facilitating a limited number of highly compatible candidates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional assessment methods are used to evaluate job seekers, then a large pool of applicants can be screened, but the assessments produce dissimilar results in different formats making comparison difficult
Solution Approach 1:
The patent transforms assessment results from various formats (scores, codes, rankings) into a unified numerical scale by establishing equivalence relationships between different assessment types. This parameter transformation enables direct comparison of job seekers across different assessments while maintaining the ability to screen large numbers of applicants.
2Measurement precision
If employers review all job seekers manually, then comprehensive evaluation is possible, but the time and resources required become excessive
Solution Approach 1:
The patent segments the candidate evaluation process into automated comparison operations and manual review stages. The system automatically compares job seeker attributes against position requirements using standardized parameters, pre-screening candidates before employers review the final ranked list, thus reducing time loss while maintaining evaluation accuracy.
Solution Approach 2:
The patent introduces a facilitator as an intermediary between employers and job seekers. This facilitator performs the standardized assessment comparisons and candidate ranking, allowing employers to focus on reviewing a limited number of pre-screened candidates rather than manually evaluating all applicants.
3Loss of information
If multiple different assessments are used to evaluate job seekers, then comprehensive suitability data is collected, but the data formats differ making normalization difficult
Solution Approach 1:
The patent creates a universal assessment framework where multiple different assessment types (personality tests, skills assessments, behavioral evaluations) are all mapped to a common set of standardized parameters. This universal structure allows comprehensive suitability data collection while simplifying normalization through a single reference framework.
Data Source
AI summary
A method of facilitating a match between an employer with at least one job opening and job seekers is provided. The employer has a set of position preferences related to the job opening. The job seekers have suitability data, resumes, etc., that are provided to the employer. The suitability data includes normalized assessment data. The method includes the steps of: determining a position quotient based on the position preferences; deriving a performance quotient for each job seeker; comparing each the performance quotient to the position quotient; and ranking each the job seeker based on the comparison of the performance quotient to the position quotient.