Profile Matching for Unstructured Documents via Keyword Weighting
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Solution Overview
Problem
Existing systems face challenges in efficiently evaluating large volumes of unstructured electronic documents against objective criteria, such as resumes for job positions, due to the flexible nature of natural language and the need for structured document formats, leading to time-consuming manual evaluation processes.
Innovation Solution
A method for profile matching in unstructured documents involves defining criteria, scanning for keywords and phrases, analyzing their statistics, and assigning point values to rank and categorize documents based on conformity to requirements, using a software system that can process unstructured documents like resumes and generate a list of matching candidates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Difficulty of detecting and measuring
If structured documents (XML) are used for profile matching, then document readability by computing systems is improved, but document format flexibility deteriorates
Solution Approach 1:
The patent introduces an intermediary component that converts unstructured natural language documents into a structured format suitable for computational processing. This mediator translates the flexible unstructured format into a readable structured format without requiring the original document to be pre-formatted, thus resolving the contradiction between maintaining document flexibility and achieving system readability.
2Measurement precision
If manual document evaluation is performed, then evaluation accuracy is improved, but processing time deteriorates
Solution Approach 1:
The system enables self-service automated evaluation where the computational system independently performs document analysis, keyword matching, and profile scoring without requiring manual human intervention. This self-service approach maintains evaluation accuracy through systematic criterion application while dramatically reducing processing time by eliminating manual reading and evaluation steps.
3Measurement precision
If extensive data input is required for profile building, then profile matching accuracy is improved, but user effort deteriorates
Solution Approach 1:
The patent extracts essential evaluation criteria and keywords from the comprehensive set of possible attributes, focusing on the most critical factors for profile matching. This extraction approach maintains profile matching accuracy by concentrating on key discriminative features while reducing user effort by eliminating the need to input extensive data across numerous fields.
4Productivity
If automated rule-based evaluation is implemented, then processing efficiency is improved, but rule definition complexity deteriorates
Solution Approach 1:
The system transforms the complex rule definition problem into parameter-based configuration by allowing users to specify evaluation criteria through simple parameters such as keyword lists, weightings, and threshold values rather than requiring complex logical rules. This parameter change approach maintains processing efficiency through automated evaluation while reducing rule definition complexity to basic parameter specification.
Data Source
AI summary
A method, system, and computer program product are disclosed for automatically matching the profile of unstructured electronic documents to objective sets of criteria. The is accomplished by evaluating text in the documents, comparing it to a set of weighted keyword criteria, generating a rating based on adherence to the criteria, rating and categorizing the results, sorting and viewing the results based on user defined criteria.