Standardized Profile Matching for Non-Standard Data Sets
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Solution Overview
Problem
Conventional online recruiting systems are inefficient in matching job seekers' resumes with suitable job postings, requiring time-consuming manual review and evaluation, as they lack the ability to effectively compare and rank non-standardized data sets.
Innovation Solution
A system and method that processes non-standardized data sets by parsing them into standardized profiles, identifying attributes, and ranking them based on metrics such as band position, occurrences, and support values, allowing for efficient comparison and matching of resumes and job postings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review and evaluation of resumes is used, then matching accuracy can be maintained, but time consumption and effort increase significantly
Solution Approach 1:
The patent introduces standardized profiles as an intermediary layer between raw resumes and matching algorithms. These profiles contain structured, normalized data that enables automated comparison while preserving matching accuracy. The standardized profile acts as a mediator that transforms unstructured resume data into a format suitable for efficient computational matching.
Solution Approach 2:
The system transforms resumes by changing their parameter representation from unstructured text to standardized structured data with defined attributes and metrics. This parameter transformation enables automated processing while maintaining the essential information needed for accurate matching between job seekers and employers.
2Adaptability or versatility
If non-standardized data sets are processed directly, then data diversity is preserved, but comparison and matching efficiency decrease
Solution Approach 1:
The patent segments resumes into standardized profiles with distinct components (personal information, work experience, education, skills). This segmentation preserves the diversity of original data while organizing it into comparable units that can be efficiently processed and matched against job postings.
Solution Approach 2:
The standardized profile serves multiple functions: it preserves diverse original data formats, enables efficient automated comparison, maintains data integrity, and supports various matching criteria. This universal structure handles different resume formats while enabling consistent processing across all inputs.
3Speed
If automated matching systems are implemented, then processing speed increases, but the ability to handle non-standardized data formats decreases
Solution Approach 1:
The standardized profile acts as an intermediary that accepts diverse non-standardized data formats and transforms them into a uniform structure suitable for automated processing. This mediator layer enables automated matching systems to handle varied resume formats without sacrificing processing speed or adaptability.
Data Source
AI summary
A system and method is described for receiving a plurality of non-standardized data sets and generating respective plurality of standardized profiles that can be used for efficiently comparing and matching one profile against the other plurality of profiles. One application of this invention is to convert job seekers' resumes and job postings into respective profiles and then permitting either a job seeker to search for job postings that most closely match the job seeker's resume or, conversely, permitting an employer to search for job seekers whose resumes most closely match the employer's job posting.