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Task assignment using ranking support vector machines

机译:使用排名支持向量机的任务分配

摘要

A method of ranking workers for an incoming task includes recording a list of completed tasks in a computer data structure, extracting first attributes from the list for the tasks that were completed during a pre-determined period, generating a first feature vector for each task and worker from the first extracted attributes, training a Support Vector Machine (SVM) based on the feature vector to output a weight vector, extracting second attributes from an incoming task, generating a second feature vector for each worker based on the second extracted attributes, and ranking the workers using the second feature vectors and the weight vector. The first attributes may be updated during a subsequent period to re-train the SVM on updated first feature vectors to generate an updated weight vector. The workers may be re-ranked based on the second feature vectors and the updated weight vector. Accordingly, the feature vectors are dynamic.
机译:一种对传入任务的工作人员进行排名的方法,包括在计算机数据结构中记录已完成任务的列表,从列表中提取在预定时间段内完成的任务的第一属性,为每个任务生成第一特征向量以及从第一提取的属性中提取工作人员,基于特征向量训练支持向量机(SVM)以输出权重向量,从传入的任务中提取第二属性,基于第二提取的属性为每个工作人员生成第二特征向量,以及使用第二特征向量和权重向量对工人进行排名。可以在随后的时间段期间更新第一属性,以在更新的第一特征向量上对SVM进行重新训练以生成更新的权重向量。可以基于第二特征向量和更新的权重向量对工人进行重新排名。因此,特征向量是动态的。

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