Job Search Relevance via Behavioral Preference Filtering
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Solution Overview
Problem
Current online job listing services often provide irrelevant job listings to jobseekers, as relevant listings may be buried in search results or require additional webpage navigation, leading to missed opportunities for more suitable positions.
Innovation Solution
A system and method that utilizes user preferences, gathered from previous searches, resumes, and online behavior, to filter and prioritize job listings, incorporating a search engine and relevance engine to provide a refined list of relevant job listings based on explicit and implicit preferences stored as keywords or in user profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If job listings are provided based on simple keyword matching, then the search process is fast and simple, but the relevance of job listings to the jobseeker decreases
Solution Approach 1:
The system performs preliminary actions by collecting and analyzing jobseeker behavior data (searches, views, applications) before generating job listings. Preference data is gathered and stored in advance, allowing the system to filter and rank listings based on inferred preferences without adding complexity to the actual search process
Solution Approach 2:
The patent introduces preference data as an intermediary element between the jobseeker and job listings. This preference data, derived from behavioral analysis, acts as a mediator that connects jobseeker needs with appropriate listings, improving relevance without requiring direct complex interaction between the user and the entire job database
2Reliability
If all matching job listings are displayed, then completeness of results is improved, but the time to find relevant listings increases
Solution Approach 1:
The system extracts and prioritizes the most relevant job listings from the complete set of matching listings based on preference data. By taking out and highlighting the top matches first, the system ensures completeness is maintained while reducing the time needed to find relevant jobs, as users see the most relevant options immediately
Solution Approach 2:
The system performs preliminary filtering and ranking of job listings based on preference data before presenting results to the user. This preliminary action organizes the complete set of matches in order of relevance, allowing users to find suitable jobs faster while maintaining access to all matching options
3Measurement precision
If preference data collection is implemented, then job listing relevance is improved, but system complexity increases
Solution Approach 1:
The system implements self-service by automatically collecting preference data from jobseeker behavior without requiring explicit user input. The system autonomously analyzes search patterns, views, and applications to build preference profiles, improving matching accuracy while avoiding the complexity of manual preference configuration interfaces
Solution Approach 2:
The system uses feedback from jobseeker interactions (searches, views, applications) to continuously refine preference data. This feedback loop automatically improves job matching accuracy over time, with the system learning from user behavior patterns without requiring complex manual intervention or reconfiguration
Data Source
AI summary
Methods and systems of providing a job search to a jobseeker are disclosed. Based on previously stored user preferences, job listings can be presented to users. User preferences can be gathered through previous search requests, resume keywords, jobseeker applies to job listings, jobseekers viewing job listings, etc. The search request can include search criteria. As such, preference data related to the jobseeker is identified based on jobseeker online behavior. In one embodiment, a set of jobs listings having associated metadata that match the search criteria is identified. A subset of job listings that match the preference data is identified. The subset of job listings is a subset of the set of job listings. At least the subset of job listings can be provided to the jobseeker. In another embodiment, a set of job listings having associated metadata that match the search criteria and the jobseeker preferences is identified and provided to the jobseeker.