Crowdsourcing market-oriented task allocation method based on fitness

Abstract

The invention discloses a crowdsourcing market-oriented task allocation method based on fitness. The method comprises the following steps: problem background definition: giving a problem background and definition for allocating picture classification tasks in the field of crowdsourcing knowledge acquisition; crowdsourcing task difficulty determination: using WordNet for calculating depth information of candidate tags, and calculating influences of all parts with the help of a polynomial function and a sigmoid function; worker ability evaluation: performing Max-Min normalization processing on the accuracy of the workers under each grade to further refine the worker performance; and optimal allocation scheme generation: converting an allocation problem between workers and tasks into a weighted bipartite graph matching model, measuring the fitness between the tasks and the workers by using a weighted Euclidean distance with a penalty factor, and solving the model by using a Kuhn-Munkres (KM) algorithm. According to the invention, the crowdsourcing platform can be helped to improve the task completion effect in the initial task distribution stage, and the crowdsourcing task completion accuracy is ensured by providing a group of effective task allocation schemes.

Description

technical field [0001] The present invention relates to a task allocation method based on fitness for the crowdsourcing market, especially a task allocation method based on fitness for picture classification tasks, relates to an optimal selection problem of a task allocation scheme, and belongs to the background of crowd intelligence resource optimization under the coordination field. Background technique [0002] With the rapid development of crowdsourcing, many crowdsourcing platforms have emerged at home and abroad, such as Youdao Crowdsourcing, Amazon Mechanical Turk (MTurk), Microworkers, etc. Through the crowdsourcing platform, users can easily publish and accept various tasks, including input, modification, and verification of given information. Therefore, with the support of online platforms, the crowdsourcing model has been widely used in image annotation, audio recognition, paragraph translation and other fields, and the image classification task in the field of c...

AI Technical Summary

Problems solved by technology

Under normal circumstances, for entry-level general concepts, most people can easily make quick judgments based on common sense. On the contrary, it is difficult to give correct answers to specific options that are far beyond their cognition.

Therefore, it is obvious that random assignment directly to the above-mentioned image classification task is not an effective strategy, which will cause those difficult tasks with specific specific candidates to be assigned to general users who do not have the relevant knowledge background, thereby seriously reducing the task completion rate. effect and waste limited human resources

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