Intelligent Test Question Recommendation System for Recruitment
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Solution Overview
Problem
The efficiency of providing test questions in talent recruitment processes is low due to the time-consuming nature of question setting by interviewers.
Innovation Solution
A method and apparatus that utilize a skill entity depth model and entity relationship network to acquire and weight skill entities from recruitment data, allowing for the intelligent recommendation of test questions from a question bank, improving the efficiency of question provision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If interviewers manually set test questions, then the questions can be customized to specific needs, but the efficiency of providing test questions is low
Solution Approach 1:
The system enables automatic generation of test questions by extracting skill entities from recruitment data and automatically matching them with relevant questions from a question bank, eliminating the need for manual question setting by interviewers while maintaining customization through skill-based matching
Solution Approach 2:
The manual mechanical process of interviewers setting questions is replaced by an automated system using depth models and entity relationship networks to extract skills and generate appropriate test questions, significantly improving efficiency
2Measurement precision
If a depth model is used to extract skill entities from recruitment data, then the accuracy of skill identification is improved, but the system complexity increases
Solution Approach 1:
An entity relationship network is introduced as an intermediary layer between the depth model and the question bank, organizing skill entities with their relationships (subordinate, equivalent, etc.) to manage complexity while maintaining high accuracy in skill identification and matching
Data Source
AI summary
Embodiments of the present disclosure provide a method and apparatus for recommending a test question, and an intelligent device. The method includes: acquiring a plurality of skill entities of a post; calculating, according to the data of the post, a weight value of each of the plurality of skill entities; and acquiring, according to the weight value of each skill entity, a recommended test question of the post from a question bank.