Real task allocation method applied to preference crowd-sourcing system

A task allocation algorithm and task allocation technology, applied in data processing applications, instruments, resources, etc., can solve the problem of scarcity of high-quality crowdsourcing workers

Inactive Publication Date: 2017-01-11
安徽慧达通信网络科技股份有限公司
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AI Technical Summary

Problems solved by technology

This competitive market for requesters may be caused by the scarcity of crowdworkers, especially high-quality crowdworkers

Method used

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  • Real task allocation method applied to preference crowd-sourcing system
  • Real task allocation method applied to preference crowd-sourcing system
  • Real task allocation method applied to preference crowd-sourcing system

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Embodiment Construction

[0062] Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0063] A crowdsourcing system model with preferences, the execution process is as follows figure 1 As shown, the specific steps are as follows:

[0064] Step 201: The crowdsourcing platform issues a triple (W, C, I) to all task requesters. Where W={1,2,...,m} represents the set of crowdsourcing workers, C=(C 1 ,C 2 ,...,C m ) represents the vector composed of the workload of m crowdsourcing workers, I=(I 1 , I 2 ,...,I m ) represents a vector composed of effort indicators of m crowdsourcing workers;

[0065] Step 202: Set the set of requesters as R={1,2,...,n}, each requester i submits a request B to the platform i =(t i ,c i ,a i ,P i ), where t i is the task issued by task requester i. c i > 0 is task t i workload. each task i have a task type associated with it a i . is the set of preferences declared by requester i; ...

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Abstract

The invention discloses a real task allocation method applied to a preference crowd-sourcing system. A preference crowd-sourcing system model is put forward, the model has multiple preference task requesters, and each task requester submits one task. Each task has different work load, and the value of each task is related to the difficulty of the task and the effort level of a crowd-sourcing worker executing the task. Regarding the model, the invention further provides a real task allocation method, having the target of maximizing the total value of the allocated task. The real task allocation method is mainly composed of two core algorithms: a task allocation algorithm based on value greed and a task allocation algorithm based on value density greed. The real task allocation method is a random algorithm established over the two core algorithms. The real task allocation method has the characteristics of calculation effectiveness, work load feasibility, preference reality and constant factor approximation ratio.

Description

technical field [0001] The invention relates to a method for assigning tasks in a crowdsourcing system, and belongs to the intersecting field of the Internet and algorithmic game theory. Background technique [0002] Crowdsourcing has become the main implementation mechanism for many Internet resources by integrating unknown users on the Internet to complete tasks that are difficult for machines to complete. At present, crowdsourcing has been widely used in information retrieval, artificial intelligence, video analysis, knowledge mining, smart city, human-computer interaction learning, image quality assessment and other fields. [0003] The design of the incentive mechanism in the crowdsourcing system is very critical. When crowdsourcing workers perform tasks, they will pay a certain cost. The incentive mechanism encourages crowdsourcing workers to participate in the crowdsourcing system and complete crowdsourcing tasks with high quality by distributing the benefits of crow...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/06
CPCG06Q10/06311
Inventor 李晓燕
Owner 安徽慧达通信网络科技股份有限公司
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