Task acceptance simulation method for labor crowdsourcing platform

Abstract

Provided is a task acceptance simulation method for a labor crowdsourcing platform. The method includes the following steps of clustering member groups according to member information of the crowdsourcing platform and historical participation task information by using projection pursuit evaluation and combination; delimiting simulation areas, determining the number of different member groups, locations and rewards of task points, and randomly generating initial positions; according to the different types of member groups and a cellular automata theory, designing corresponding evolution rules respectively, evolving according to the rules, and simulating a task accepting process; after the simulation is completed, extracting the member information applied of each task point, using an ideal point method for evaluation, and proving suggestions for improvement. The method simulates acceptance conditions of tasks in the crowdsourcing platform from a microscopic point of view, considers a plurality of influencing factors and historical prior information, has high simulation precision and reasonable calculation amount, and can provide reference basis for defining task rewards and task ranges.

Description

technical field [0001] The invention relates to the technical field of labor crowdsourcing platforms, in particular to a method for simulating task acceptance of labor crowdsourcing platforms. Background technique [0002] With the rise of the mobile Internet and big data, people's demand for data is far greater than ever. In recent years, with the rise of crowdsourcing model. People set rewards by posting tasks on the crowdsourcing platform, and gather the wisdom of participating members of the platform to help complete the tasks. For members, they can do some tasks within their spare time to get a certain reward. For companies that issue tasks In other words, the crowdsourcing model has the characteristics of low cost and immediacy compared with specialized companies or platform services, and is more and more popular among people. The main task types of the current crowdsourcing platform include data collection, posting tasks, and attracting members to extract data in th...

AI Technical Summary

Problems solved by technology

[0003] However, crowdsourcing platforms often face situations such as low task application and poor quality of some tasks. For crowdsourcing platforms, increasing pricing or reducing task difficulty is an important means to attract high-quality members to participate in tasks

In the past, the pricing schemes of tasks were all derived from the macroscopic probability, without considering the relationship between individual members at the microscopic level

However, there is a lack of simulation solutions for the acceptance of tasks on crowdsourcing platforms, and most of them are considered from a macro perspective, which ignores the mobility of members themselves and ignores different groups of members, resulting in low accuracy and lack of simulation Analysis and utilization of the results

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