接诉即办智能派单业务调度算法研究  

Study on Scheduling Algorithm of Intelligent Order Dispatching

作　　者：贾经冬[1] 张敏南 赵祥 黄坚[1] JIA Jingdong;ZHANG Minnan;ZHAO Xiang;HUANG Jian(School of Software,Beihang University,Beijing 100191,China)

机构地区：[1]北京航空航天大学软件学院,北京100191

出　　处：《计算机科学》2023年第S02期937-943,共7页Computer Science

基　　金：国家重点研发计划项目:政法智能协同技术支撑体系与应用示范研究(2020YFC0833400)。

摘　　要：随着国家数字化建设的发展,社会治理的智能化、专业化也成为城市科技进步的基本要求,各政府系统须要对人民的诉求做到高效精确的处理。而从当前的各大政府门户网站的诉求通道收集的民众诉求信息,均是通过人工方式判断责任部门,然后将其手动分配给相关部门进行后续问题的核实和处理,大大限制了诉求处理的效率和准确性。而接诉即办智能派单算法利用人工智能和深度学习方法,基于真实的民众诉求信息数据进行训练,自动精准而高效地将诉求分派到相关部门进行后续审查处理,加快了政务处理流程的速度并大大降低了不必要的人力成本,因此该智能调度算法的研究有着重要意义。首先,通过数据去噪和脱敏,将数据进行层级拼接,构建数据标签和标准流程库以进行标签对齐。然后,基于公开数据集训练地址识别基线模型,在工单分类中提出基于类别比例采样的标签融合方法解决数据类不平衡问题,实验结果显示在基线模型的基础上提高了数十个百分点。最后,结合分类模型和地址识别模型,构建智能回复模板,完成接诉即办智能派单的全流程。With the development of national digital construction,the intellectualization and specialization of social governance have become the basic requirements for the progress of urban science and technology.All government systems need to deal with the demands of people efficiently and accurately.However,the public appeal information collected from the appeal channels of major government portals is manually judged by responsible departments and then manually assigned to relevant departments for follow-up verification and processing,which greatly limits the efficiency and accuracy of appeal processing.Using artificial intelligence and deep learning methods,the intelligent dispatching algorithm based on real public demand information data training,accurately and efficiently dispatches demands to relevant departments,accelerates the speed of government affairs processing process and greatly reduces unnecessary labor costs.Therefore,the research of this scheduling algorithm is of great significance.First,the data is denoised and desensitized,and hierarchical stitching is used to build data labels and standard process libraries for label alignment.Then,a baseline model for address recognition is trained on publicly available datasets,and a label fusion method based on category proportion sampling is proposed to solve the problem of imbalanced data in work order classification.Experimental results show that the method improves the baseline model by varying degrees.Finally,combining the classification model and the address recognition model,an intelligent response template is constructed to complete the entire process of intelligent dispatching for complaint handling.

关 键 词：智能派单 类不平衡 标签融合 BERT模型 深度学习 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]