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Crowdsourcing task pricing optimization method and system for mobile platform

A mobile platform and optimization method technology, applied in the field of data analysis, can solve problems such as unreasonable pricing and server pressure

Inactive Publication Date: 2018-05-04
SHANDONG NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above problems, the present invention provides a mobile platform crowdsourcing task pricing optimization method and system. The present invention performs data visualization, data analysis and feature optimization, task pricing model optimization, and evaluation optimization model for the data of crowdsourcing task completion. Performance, finally determine the task pricing optimization method of the mobile Internet self-service crowdsourcing platform, and solve the problem of server pressure caused by unreasonable pricing

Method used

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  • Crowdsourcing task pricing optimization method and system for mobile platform
  • Crowdsourcing task pricing optimization method and system for mobile platform
  • Crowdsourcing task pricing optimization method and system for mobile platform

Examples

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Embodiment 1

[0062] Such as figure 1 As shown, the present invention provides a mobile Internet platform crowdsourcing task pricing optimization method. One embodiment of the present invention is to set the price for tasks in the "Photographing and Making Money" APP. "Make money by taking photos" is a self-service model under the mobile Internet. The user downloads the APP, registers as a task demander of the APP, and then receives a task that needs to be photographed from the APP (such as going to a supermarket to check the availability of a certain product), and earns the remuneration specified by the APP for the task.

[0063] (1) Data visualization: collect mobile Internet self-service crowdsourcing data, visualize and preprocess the data;

[0064] This implementation collects the task item data and task demander information data of the "Photograph to Make Money" APP. The completed task item data includes the location (indicated by latitude and longitude), pricing and completion stat...

Embodiment 2

[0104] (2-8) According to the location of the cities displayed in (1), after consulting the data, we obtained the corresponding GDP data of Guangzhou, Shenzhen, Dongguan and Foshan in Guangdong Province in 2016, as shown in Table 3. According to the GDP values ​​of the four cities, the four cities are divided into four levels, as shown in Table 4:

[0105] Table 3 GDP value of cities in Guangdong Province in 2016

[0106] city

[0107] Table 4 GDP grades of cities in Guangdong Province in 2016

[0108] city

[0109] In the described step (2-9), feature expansion includes: extended task demander reputation information (mean value, variance, standard deviation, maximum value, minimum value, mode, mode number, mode number ratio ), the extended linear distance information between the position of the task demander and the task position (mean value, variance, standard deviation, maximum value, minimum value, mode, mode number, mode number ratio), extended task r...

Embodiment 3

[0111] In described step (2-10), use filtering method to carry out feature selection, to the feature in (2-9), utilize variance selection method to carry out feature selection, set threshold value to be 10, select the feature with variance greater than threshold value, as The final selected features are used to optimize the pricing model. There are a total of 39 features selected in this example, mainly including the number of task demanders within the analysis range, the credibility information of task demanders (mean value, variance, standard deviation, maximum value, minimum value, mode, mode number, The proportion of the mode number), the distance information between the position of the task demander and the task position (mean value, variance, standard deviation, maximum value, minimum value, mode number, mode number, mode number proportion), task Demanders can book task quota information (mean value, variance, standard deviation, maximum value, minimum value, mode number...

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Abstract

The invention discloses a crowdsourcing task pricing optimization method and system for a mobile platform. The crowdsourcing task pricing optimization method includes step (1): data collection: collecting crowdsourcing task information and task demander information of a labor service crowdsourcing platform, and visualizing and preprocessing the crowdsourcing task information; step (2): performingmulti-angle analysis on the data information collected in step (2), and optimizing influencing factors of the task pricing; sep (3): taking characteristics determined in step (2) as an input value ofa GBDT algorithm, taking a task pricing model as an output value of the GBDT algorithm, and using the GBDT algorithm to establish the task pricing model; and step (4): using the task pricing model toperform pricing. According to the mobile platform crowdsourcing task pricing optimization method and system, data visualization and feature optimization and task pricing model optimization are performed on the data on crowdsourcing task finishing conditions, the performance of the model is evaluated and optimized, and finally the task pricing optimization method for the mobile internet self-service labor service crowdsourcing platform is determined.

Description

technical field [0001] The present invention relates to the technical field of data analysis, in particular to a pricing optimization method and system for crowdsourcing tasks on a mobile platform. Background technique [0002] In today's society, the mobile Internet has become a very important terminal for information acquisition. Using the crowdsourcing model, the complex research business execution chain is transferred to the mobile platform for implementation, so that many APP users can directly receive tasks, execute and give feedback on the mobile platform. It not only provides various business inspection and information collection services for enterprises, but also effectively guarantees the authenticity of survey data, shortens the survey cycle, and reduces the cost of survey business implementation. Among them, the formulation of task pricing is very important. Appropriate pricing will attract users to receive tasks and improve task completion. [0003] The problem...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q30/02G06Q30/06
CPCG06Q10/04G06Q30/0283G06Q30/0639
Inventor 马璐璐王红宋永强刘海燕王露潼王倩余晓梅闫晓燕胡斌
Owner SHANDONG NORMAL UNIV
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