METHOD FOR AUTOMATICALLY GENERATING A WORKER POOL BASED ON THE FUNCTIONAL ELEMENTS AND DIFFICULTY OF CROWDSOURCING BASED PROJECTS FOR ARTIFICIAL INTELLIGENCE TRAINING DATA GENERATION

摘要

A method for automatically generating worker pools based on the functional elements and difficulty of a crowdsourcing-based project for generating artificial intelligence learning data is provided. The method identifies the functional elements of a plurality of completed crowdsourcing-based projects (hereinafter, "first project"), and evaluates the difficulty of the plurality of first projects by using the work history of the plurality of first projects, Based on the functional elements and difficulty, a pool of workers including a plurality of workers who have clustered a plurality of first projects into a plurality of clusters, and participated in one or more first projects belonging to each cluster for each cluster (hereinafter , "Templated worker pool") is created by templated. Then, the functional elements of the crowdsourcing-based project to be opened (hereinafter, "the second project") are identified, the difficulty of the second project is evaluated using the pilot work of the second project, and the functional elements of the second project and One of the plurality of clusters is selected based on the difficulty level, and the templated worker pool of the selected cluster is applied as the worker pool of the second project. Thereafter, a second project is opened, a plurality of tasks of the second project are assigned to a plurality of workers in the worker pool to request the task performance, and a plurality of task results are input from a plurality of workers in the worker pool.