O*NET Code Assignment for Job Search Precision
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Solution Overview
Problem
Job seekers face difficulties in finding relevant job postings due to the variability of job titles and the lack of O*NET codes in job postings, making it hard for search software to narrow down searches effectively.
Innovation Solution
A system and method that extracts fields from job postings and determines a specific O*NET code for each posting, using job bots to visit network sites, extract data, and store it in a searchable database, allowing job seekers to find relevant positions by matching job titles and descriptions with O*NET codes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If job seekers manually search multiple job posting websites using various keywords, then they can find job openings, but the search process becomes time-consuming and returns many irrelevant results due to job title variability
Solution Approach 1:
The system performs preliminary classification by automatically assigning O*NET codes to job postings during data collection. This pre-processing step categorizes jobs before job seekers perform their searches, eliminating the need for manual keyword-based filtering and significantly reducing search time while improving efficiency.
2Adaptability or versatility
If job postings use varied job titles to describe similar roles, then they can be more descriptive, but it becomes difficult for search software to identify relevant positions
Solution Approach 1:
The O*NET code serves as an intermediary standard that bridges the gap between diverse job titles and standardized classification. The system maps various job titles to their corresponding O*NET codes, enabling accurate matching while preserving the flexibility of descriptive job titles in the original postings.
3Quantity of substance
If job posting databases collect data from multiple network sites, then they contain more job openings, but the complexity of extracting and standardizing data from different formats increases
Solution Approach 1:
The system implements a universal data extraction framework that handles multiple website formats through standardized parsing routines. By using adaptable extraction logic that can accommodate different HTML structures and data formats, the system collects job postings from numerous sources without proportionally increasing complexity.
4Measurement precision
If O*NET codes are manually assigned to each job posting, then classification accuracy improves, but the processing time and labor requirements increase significantly
Solution Approach 1:
The system employs automated algorithms that extract job title information and autonomously assign corresponding O*NET codes without human intervention. This self-service approach maintains high classification accuracy while dramatically increasing processing speed and eliminating manual labor requirements.
Data Source
AI summary
Systems, methods and computer program products include job bots that are configured to periodically visit network sites that have stored therein one or more job postings. During each visit, the one or more job postings are analyzed and a searchable job post database is updated to add new job postings, modify changed job postings and delete any removed job postings. A search engine is provided for job seekers to search the searchable job post database where a consolidate list of job postings from the network sites is stored.