Work platform task workload prediction method based on feedback correction

A working platform and forecasting method technology, applied in forecasting, instrumentation, data processing applications, etc., can solve problems such as data not being updated in time, evaluation results with too much error, and platform users cannot be satisfied, so as to improve accuracy and improve data quality. Basis, evaluate the effect of high accuracy

Pending Publication Date: 2020-09-11
武汉空心科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] When the contracting party releases the task, the task cost is entrusted on the platform, and the platform estimates the workload, but when estimating the workload, because the original data cannot be updated in time, the factors affecting the workload have changed to a certain extent, and the platform uses The workload evaluation results obtained by the unified prediction model are less accurate, and in some scenarios, the evaluation results have too large errors, which cannot meet the requirements of platform users

Method used

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  • Work platform task workload prediction method based on feedback correction
  • Work platform task workload prediction method based on feedback correction
  • Work platform task workload prediction method based on feedback correction

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0033] refer to Figure 1-3 , a method for predicting the workload of work platform tasks based on feedback correction, including the following steps:

[0034] S1: Receive work tasks, the contracting party publishes the work task requirements to the work platform, and the work platform receives various tasks;

[0035] S2: Screen work tasks, conduct preliminary screening of work tasks, and reject some tasks that cannot be completed;

[0036] S3: Task classification, after counting all tasks, classify them, and initially divide them into three categories: general purpose, industrial design and software development;

[0037] S4: Evaluate the work content, evaluate the work content of the receiving task, and the evaluation is classified into content evaluation, complexity evaluation, and similarity evaluation;

[0038] S5: Data analysis, comparing the original data, comparing some variables in the existing work tasks with the original data, to re-analyze the workload situation, ...

Embodiment 2

[0044] refer to Figure 1-3 , a method for predicting the workload of work platform tasks based on feedback correction, including the following steps:

[0045] S1: Receive work tasks, the contracting party publishes the work task requirements to the work platform, and the work platform receives various tasks;

[0046] S2: Screen work tasks, conduct preliminary screening of work tasks, and reject some tasks that cannot be completed;

[0047] S3: Task classification, after counting all tasks, classify them, and initially divide them into three categories: general purpose, industrial design and software development;

[0048] S4: Evaluate the work content, evaluate the work content of the receiving task, and the evaluation is classified into content evaluation, complexity evaluation, and similarity evaluation;

[0049] S5: Data analysis, comparing the original data, comparing some variables in the existing work tasks with the original data, to re-analyze the workload situation, ...

Embodiment 3

[0055] refer to Figure 1-3 , a method for predicting the workload of work platform tasks based on feedback correction, including the following steps:

[0056] S1: Receive work tasks, the contracting party publishes the work task requirements to the work platform, and the work platform receives various tasks;

[0057] S2: Screen work tasks, conduct preliminary screening of work tasks, and reject some tasks that cannot be completed;

[0058] S3: Task classification, after counting all tasks, classify them, and initially divide them into three categories: general purpose, industrial design and software development;

[0059] S4: Evaluate the work content, evaluate the work content of the receiving task, and the evaluation is classified into content evaluation, complexity evaluation, and similarity evaluation;

[0060] S5: Data analysis, comparing the original data, comparing some variables in the existing work tasks with the original data, to re-analyze the workload situation, ...

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Abstract

The invention discloses a work platform task workload prediction method based on feedback correction. The method comprises the following steps that a work task is received, the packet sender publishesa work task demand to the work platform; the working platform receives various tasks, the work tasks are screened out, primary screening is carried out on the work tasks, some tasks which cannot be completed are rejected, task classification is carried out, statistics on all the tasks is carried out, then the tasks are classified, the tasks are preliminarily divided into three categories of universality, industrial design and software development; work contents are evaluated, the work content of the received tasks is evaluated, and wherein evaluation and classification is content evaluation.According to the invention, detailed information in the work task can be fully understood, the detail information is accurately evaluated; the construction period evaluation error value of the actualconstruction period and the evaluation construction period is obtained through the stored data, the artificial neural network and analogy arrangement, feedback correction can be performed according to comparison of the collected information and the original data, and the task workload is re-evaluated.

Description

technical field [0001] The invention relates to the technical field of workload evaluation, in particular to a method for predicting the workload of a work platform task based on feedback correction. Background technique [0002] The work platform 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; Party starts to work after receiving the assigned subtask, and submits the work results to the platform after the subtask is completed. The platform needs to study the workload evaluation method of the task, and evaluate the workload based on the task description and related documents, so as to predict the construction period and cost. [000...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q10/06
CPCG06Q10/04G06Q10/06312
Inventor 王琦
Owner 武汉空心科技有限公司
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