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METHOD AND SYSTEM FOR SELECTING LABEL FROM PLURALITY OF LABELS FOR TASK IN CROWD-SOURCED ENVIRONMENT

机译:用于从多个标签中选择标签的方法和系统在人群源环境中任务

摘要

There is disclosed a method system for selecting a label for a task, the method comprising: receiving a plurality of labels, each of the label included within the plurality of labels being indicative of a given assessor's perceived preference of a first object of over a second object; analyzing the comparison task to determine a set of latent biasing features; executing a MLA configured to generating a respective latent score parameter for the first object and the second object, the respective latent score parameter indicative of a probable offset between the given assessor's perceived preference and an unbiased preference parameter of the first object over the second object; generating a predicted bias degree parameter for the given assessor; generating the unbiased preference parameter; using, by the server, the unbiased preference parameter as the label for the comparison task for the given assessor.
机译:公开了一种用于选择用于任务的标签的方法系统,该方法包括:接收多个标签,包括在多个标签内的每个标签,指示给定的评估员的感知偏好于一秒钟的第一个物体的感知偏好目的;分析比较任务以确定一组潜在偏置特征;执行被配置为为第一对象和第二对象生成相应的潜像参数的MLA,指示给定的评估员的感知偏好与第一个对象的感知偏好与第二个对象的不偏的偏好参数之间的相应潜在的偏移参数;为给定的评估员生成预测的偏置度参数;生成无偏的偏好参数;通过服务器使用的非偏见首选项参数作为给定评估员的比较任务的标签。

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