计算机科学与探索2025，Vol.19Issue(4)：1036-1047,12.DOI:10.3778/j.issn.1673-9418.2403017
面向12345政务热线事件分拨的深度行为语义网络
Deep Behavior and Semantic Network for 12345 Hotline Event Dispatch
摘要
Abstract
In China,citizens can seek help from the 12345 hotlines when they suffer from problems in daily life.After receiving requests from citizens,the hotline officer analyzes the demand of citizens and dispatches events to the corresponding government departments.Currently,the whole process mainly relies on manual work,which takes up a lot of human resources and leads to many incorrect dispatches.To improve the efficiency and accuracy of dispatching,in this paper,an efficient automatic data-driven event dispatch approach is proposed.Considering the historical dispatch records,event text and department responsibility,a deep behavior and semantic network(DBSN)for event dispatch is proposed.The network mainly consists of a history behavior encoding module,an event semantic learning module and a multi-dimension feature matching module.The history behavior encoding module builds a hierarchical bipartite graph network between different categories of events and departments,learning dispatch patterns through graph node embedding.The event semantic learning module uses the CNN and attention mechanism to learn the semantic information of event demand and department responsibility.The multi-dimension feature matching module matches events and departments from two dimensions including behavior and semantic features.Based on the 12345 Hotline data of a city,experimental results demonstrate the advantages of the proposed approach compared with baselines.关键词
12345政务热线/事件分拨/层次二分图/文本分类/城市计算Key words
12345 hotline/event dispatch/hierarchical bipartite graph/text classification/urban computing分类
信息技术与安全科学引用本文复制引用
陈顺,易修文,张钧波,李天瑞,郑宇..面向12345政务热线事件分拨的深度行为语义网络[J].计算机科学与探索,2025,19(4):1036-1047,12.基金项目
国家重点研发计划(2019YFB2103205) （2019YFB2103205）
北京市科技新星项目(Z211100002121119).This work was supported by the National Key Research and Development Program of China(2019YFB2103205),and the Nova Program of Beijing(Z211100002121119). （Z211100002121119）
