An employee performance evaluation and reward method and device based on automatic accounting
By receiving data through online forms and generating quantitative performance indicators using natural language processing and machine learning algorithms, the system solves the problems of low efficiency, insufficient accuracy, and delayed feedback in traditional employee performance evaluation, achieving fully automated and intelligent performance evaluation and reward calculation.
CN122134176APending Publication Date: 2026-06-02ANRUI DIGITAL INFORMATION TECH CO LTD
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- ANRUI DIGITAL INFORMATION TECH CO LTD
- Filing Date
- 2026-02-10
- Publication Date
- 2026-06-02
AI Technical Summary
Technical Problem
Traditional employee performance evaluation methods are inefficient, inaccurate, have delayed feedback, and lack in-depth insights. Existing software lacks intelligent understanding and end-to-end automation solutions.
Method used
Detailed work data is received through online forms. Natural language processing and machine learning algorithms are used for text analysis and structured cleaning to generate quantitative performance indicators. Rewards are automatically calculated based on incentive policies, and visual reports are provided.
Benefits of technology
It achieves full-process automation, improves evaluation efficiency and accuracy, provides real-time feedback and immediate incentives, supports in-depth analysis and decision-making, and is highly adaptable.
✦ Generated by Eureka AI based on patent content.
Smart Images
Figure CN122134176A_ABST
Abstract
This invention discloses a method and apparatus for employee performance evaluation and reward based on automatic calculation. The method includes: receiving real-time work detail data submitted by employees via an online form and storing the work detail data in a database; performing text analysis and structured cleaning on the work detail data from the database to generate standardized preprocessed data; training a performance calculation model using machine learning algorithms based on the preprocessed data and historical performance data, and calculating and generating quantitative performance indicators for each employee using the performance calculation model; visualizing the quantitative performance indicators and generating a performance analysis report including individual and team dimensions; and automatically calculating and generating reward calculation results for each employee based on a preset reward policy and the quantitative performance indicators in the performance analysis report.
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