Job Matching System Using Weighted Semantic Scoring
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Solution Overview
Problem
Current job search tools often require users to sift through numerous results or return no results if criteria are too specific or narrow, failing to effectively match job seekers with suitable job openings.
Innovation Solution
A job matching search tool and method that processes job-descriptor data to derive and store words, root forms, and synonyms, allowing users to classify job openings using swipe gestures, and ranks matches based on generated scores for intelligent job recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional keyword-based searching tools are used to match job seekers with job openings, then the search process becomes simple to operate, but the matching accuracy deteriorates resulting in irrelevant results or no results when criteria are specific
Solution Approach 1:
The patent transforms the matching parameters from simple keyword presence/absence to weighted semantic similarity scores. Job descriptors and candidate profiles are converted into weighted word lists where each word has an associated importance weight. The matching process calculates a composite score based on weighted overlaps between job requirements and candidate qualifications, enabling nuanced differentiation among candidates and jobs while maintaining operational simplicity through automated scoring.
2Measurement precision
If users manually review and analyze job descriptions to determine matches, then the matching accuracy improves, but the time required for the search process increases
Solution Approach 1:
The system performs preliminary processing of job descriptions and candidate profiles before the actual matching occurs. Job descriptors are pre-analyzed to extract weighted keywords and phrases that capture essential job requirements. Candidate profiles are similarly pre-processed to identify relevant qualifications. This preliminary structuring enables rapid automated matching without requiring manual review, significantly reducing search time while maintaining high matching accuracy through the pre-established weighted parameter frameworks.
3Measurement precision
If specific criteria are provided in the search to improve matching precision, then the relevance of results improves, but the quantity of search results decreases potentially to zero
Solution Approach 1:
The matching system evaluates all job descriptors and candidate profile elements, not just exact keyword matches. It calculates partial scores for each weighted word overlap, allowing candidates to receive positive match scores even if they don't meet every single criterion perfectly. The system ranks results by cumulative weighted scores, ensuring that a sufficient quantity of potentially relevant jobs are returned even when specific criteria are provided, while still maintaining high relevance through the weighted scoring mechanism.
Data Source
AI summary
A computer-implemented method and system is provided that involves storing job-descriptor data for a plurality of job openings and processing the job descriptor data to derive and store words or root forms or synonyms corresponding thereto. A job seeker user interacts with the system to review at least one job opening, which involves the user classifying at least one word or text phrase of the job-descriptor data for the at least one job opening, deriving and storing words or root forms or synonym corresponding to the at least one word or text phrase classified by the user, and ranking a set of job openings based upon scores for the set of job openings, where the scores are based on frequencies of the at least one word or text phrase classified by the user. Other features and aspects are described and claimed.