Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Working platform task workload assessment method based on big data

A work platform and work task technology, applied in data processing applications, neural learning methods, biological neural network models, etc., can solve problems such as the inability to cover system security settings, the inability to update data in time, and the inability to make predictions in time. Easy to run and use, improve work efficiency and improve accuracy

Pending Publication Date: 2021-07-16
武汉空心科技有限公司
View PDF0 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Of course, the security settings of the Internet information platform cannot cover the original security settings of the system.
[0004] The current work platform estimates the workload because the original data cannot be updated in time, and the factors affecting the workload have changed to a certain extent. The evaluation model of the work platform is relatively fixed, and the changes caused by the influence of some factors cannot be timely. Forecasting results in some differences in the evaluation of workload. Therefore, we propose a method for evaluating the workload of work platform tasks based on big data.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Working platform task workload assessment method based on big data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0034] see figure 1 Shown: the present invention is a kind of work platform task workload evaluation method based on big data, comprises the following steps:

[0035] Step1: The contracting party publishes the work task requirements to the work platform, and the work platform receives various tasks;

[0036] Step2: The work platform decomposes the tasks and searches for matching contractors from the talent pool of the work platform according to the skill requirements of each sub-task;

[0037] Step3: Assign the sub-tasks to the appropriate sub-tasks, and classify all the sub-tasks after statistics, and initially divide them into three categories: general, industrial design and software development;

[0038] Step4: Evaluate the work content of the task received by the contractor, and the evaluation is classified into content evaluation, complexity evaluation, and similarity evaluation;

[0039] Step5: Evaluate the content volume, complexity and similarity through a variety of...

Embodiment 2

[0046] Among them, the industrial design in Step3 is divided into four categories: product design, environmental design, communication design, and design management; including modeling design, mechanical design, clothing design, environmental planning, interior design, UI design, graphic design, packaging design, advertising Design, display design, website design, etc. Industrial design is also called industrial product design. Industrial design involves psychology, sociology, aesthetics, ergonomics, mechanical structure, photography, color science, etc.

[0047] Wherein, the software development in Step 3 is a process of building a software system or a software part in the system according to user requirements, and the software development is a system engineering including requirement capture, requirement analysis, design, implementation and testing.

[0048] Wherein, the content volume evaluation in Step4 is evaluated by different work contents in the task, and the evaluation...

Embodiment 3

[0054] In the present invention, the original data stored in the work platform is compared with the evaluated work content, and the work content affected by various factors is measured and calculated through the comparison, so as to re-analyze the workload and improve the accuracy of the work platform in evaluating the workload By decomposing work tasks into multiple sub-tasks, avoiding inaccurate task classification due to too few classifications, affecting later workload prediction, and improving prediction accuracy, the evaluation method based on big data in the present invention is easy to operate and easy to operate. It is simple and can effectively improve the work efficiency of work platform management.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a working platform task workload assessment method based on big data, and relates to the technical field of working platform management. According to the method, a working platform decomposes a task, searches a matched packet receiving party from a talent pool of the working platform according to skill requirements of each sub-task, and evaluates the working content of the task received by the packet receiving party, and the evaluation is classified into content evaluation, complexity evaluation and similarity evaluation. The method is convenient to operate and use and simple to operate, the working efficiency of working platform management can be effectively improved, the original data stored in the working platform is compared with the evaluated working content, the working content influenced by various factors is calculated through comparison, and the workload is reanalyzed. The accuracy of workload evaluation of a working platform is improved, the work task is decomposed into a plurality of sub-tasks, it is avoided that due to too little classification, task classification is inaccurate, and later workload prediction is affected, and the prediction accuracy is improved.

Description

technical field [0001] The invention relates to the technical field of work platform management, in particular to a big data-based work platform task workload evaluation method. Background technique [0002] The work platform of this product is an Internet platform that provides various work management related services in a crowdsourcing mode. The contracting party publishes the work task requirements to the work platform, and the platform decomposes the tasks and finds the matching sub-tasks from the platform talent pool according to the skill requirements of each sub-task, and assigns the sub-tasks to the appropriate sub-tasks; The party starts working after receiving the assigned subtasks, and submits the work results to the platform after the subtasks are completed; the contracting party receives and reviews the task delivery results. When releasing a task, the contract-sending party will entrust the task fee on the platform, and after the task is delivered and accepted...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06G06K9/62G06N3/04G06N3/08
CPCG06Q10/0631G06Q10/06393G06N3/04G06N3/08G06F18/241
Inventor 王琦
Owner 武汉空心科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com