Lets say we have an English to French translation task in a company and there are 100s of workers who are proficient in doing this task but each worker has its own unique attributes which allow them to do certain translations in a better way over others eg: A translator who is a doctor would do better translations of medical documents. Consider 1000s of documents for translation received per day and the turnaround time is 1 day per document. So there is a two fold problem
1)Allocating the tasks to available translators using a queuing model or any other efficient allocation mechanism.
2)Learning the worker model based on his past performance like correctness scores, static parameters like skill set, qualifications, experience etc using a machine learning system
So is there an setup / system / model which solves both of the above problems in one cohesive system. From my reading this problem calls for application of the assignment problem , user modelling, queuing and machine learning optimization. I am searching for existing models or frameworks which integrate all of this.