Iterative Candidate Resume Database Querying with Dynamic Threshold Adjustment
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Solution Overview
Problem
Conventional recruitment systems face challenges in identifying suitable job candidates for high-end executive roles due to reliance on specific keywords, which can lead to incomplete matches and excessive or insufficient search results, lacking diversity and accuracy in candidate selection.
Innovation Solution
A computer-implemented method and system that summarizes key accomplishments from natural language documents, clusters them, and identifies relevant clusters for a given job, using a ranked list of search terms to construct a search query that iteratively adjusts based on thresholds to ensure a balanced number of results, incorporating machine learning for optimal keyword selection and filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If keyword-based search queries are used to identify candidates, then the search can be simple and fast, but the accuracy and completeness of candidate matching deteriorates
Solution Approach 1:
The patent introduces an intermediary layer between the search query and candidate profiles. Instead of directly matching keywords to profiles, the system uses extracted key accomplishments as intermediaries to bridge the gap, enabling more accurate matching while maintaining search efficiency through automated extraction and clustering processes
2Quantity of substance
If multiple Boolean operators and search terms are applied to increase result volume, then the quantity of candidates increases, but the quality and diversity of matches deteriorates
Solution Approach 1:
The patent segments the search process into distinct phases: extracting key accomplishments from candidate profiles, clustering similar accomplishments, and then forming search queries based on these clusters. This segmentation allows the system to systematically explore different candidate pools while maintaining quality through structured filtering and ranking mechanisms
3Measurement precision
If recruiters manually adjust search terms to optimize results, then the search can be tailored to specific needs, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The patent implements self-service automation where the system automatically extracts key accomplishments from candidate profiles, clusters them into relevant groups, and generates optimized search queries without requiring manual intervention. This self-service approach maintains high search result relevance while eliminating the time-consuming manual adjustment process
4Quantity of substance
If selective search terms are used to reduce result volume, then the number of candidates decreases, but the risk of missing suitable candidates increases
Solution Approach 1:
The patent creates a dynamic search system that automatically adjusts search parameters based on the extracted and clustered accomplishments. The system can flexibly modify search queries in real-time based on the distribution and relevance of clustered accomplishments, ensuring both adequate result volume and high reliability in candidate selection without manual intervention
Data Source
AI summary
Iterative search of a candidate resume database is performed using computer-implemented methods and accompanying systems, and includes the steps of generating a ranked list of search terms associated with a job candidate search, constructing a search query of the candidate resume database based on the ranked list of search terms, executing the search query on the candidate resume database in a count mode to generate a number of results, evaluating the number of results generated from the execution of the search query by comparing the number of results to individual thresholds within a set of thresholds. Upon determining that the number of results exceeds one or more thresholds, the methods further include retrieving the results from the candidate resume database. Upon determining that the number of results does not exceed one or more thresholds, the methods further include removing a restrictive term from the search query.