Abstract
How to recruit, test and train the adaptive archive allocation system users, and how to assign the archive translation tasks to all available system users according to the optimal matching principle are still a problem that needs to be solved. With the help of proper names and terms in China’s Imperial Maritime Customs archives, this paper aims to solve the problem. When the corresponding translation, domain or attributes of a proper name or term is known, it will be easier for some archive translation tasks to be completed, and the adaptive archive allocation system will also improve the efficiency of archive translation task allocation and the quality of archive translation tasks. These related domains or attributes are different labels of these archives. To put it simply, multi-label classification means that the same instance can have multiple labels or be labeled into multiple categories, which is called multi-label classification. With the multi-label classification, archives can be classified into different categories, such as the trade archives, preventive archives, personnel archives, etc. The system users are divided into different professional domains by some tests, for instance, system users who are good at economic knowledge and users who have higher language skills. With these labels, the adaptive archive allocation system can make the optimal match between the archives and system users, so as to improve the efficiency and quality of archive translation tasks. In this paper, through multi-label classification, the adaptive archive allocation system can realize the optimal allocation of archive translation tasks to the system users. The optimal allocation is realized through the construction of optimization control model, and verifies that the adaptive archive allocation system can improve the performance of task allocation over time without the participation of task issuers.
Methods of Thrust Allocation in a DP Simulation System of Maritime University of Szczecin