基于自适应分配模型的查新系统

Novelty search system based on adaptive task allocation model

针对一般查新系统中存在的当项目申请量大时任务分配效率降低从而影响查新进程的问题,通过分析农业科技文献查新室多年查新数据与工作流程,并对其实际工作需求详细调研,提出了一种基于指标权重叠加的自适应分配模型(ATAM)与算法,并设计实现了基于此模型的农业科技文献查新系统。最终测试结果表明,采用该模型的查新系统能够一定程度地减少任务管理的工作量,缩短任务分配时间,加速查新流程。

With regard to the problem that low tasks allocation efficiency influence the process of novelty search in general novelty search system when they face a large number of tasks. Through the analysis of the data and the working process of agricultural science and technology literature novelty search office, and the detailed investigation of actual work, this paper put forward an Adaptive Task Allocation Model （ATAM） and algorithm based on index weight stack, designed and implemented the agricultural science and technology literature novelty search system based on the model. The final test shows that, using the model, the system can greatly reduce the workload of task management, reduce the time of task allocation and accelerate the novelty search process.