基于轨迹语义的船舶活动知识图谱构建

Construction of Ship Activity Knowledge Graph Using Trajectory Semantics

随着全球经济一体化的深入推进,海上交通拥堵和船舶事故频发。为了对海上船舶活动进行监管和分析,传统的方法主要利用船舶定位数据进行数据挖掘,未结合其他海上多源数据进行船舶时空活动过程和行为模式分析,缺少深层次的知识挖掘。为此,本文综合利用多源数据,在提取轨迹的语义信息基础上,构建船舶活动知识图谱,为低知识密度的轨迹时空点序列向高阶语义知识转化提供一种有效途径。具体地,首先通过解析船舶活动的特征和组成要素,基于“过程-事件-行为”的核心思想,设计船舶活动知识图谱本体层;然后利用Stop/Move模型提取轨迹语义信息,利用DMCNN模型抽取船舶突发事件,完成实例层填充;最后通过构建原型系统,对上述模型和方法进行验证。结果表明,本文所构建的船舶活动知识图谱,可以支持对船舶常规活动和突发事件进行知识表示,并可以实现时空活动查询和回溯,进而达到语义增强效果,具有一定的应用价值。

With the deepening of global economic integration,maritime traffic congestion and ship accidents occur frequently.In order to supervise and analyze the marine ship activities,the traditional methods mainly use the ship positioning data for data mining without combining other marine multi-source data for the analysis of ship spatiotemporal activity process and behavior pattern,and thus lack deep knowledge mining.Therefore,this paper makes comprehensive use of multi-source data and constructs the ship activity knowledge map based on extracting the semantic information of trajectory,which provides an effective way for the transformation of trajectory spatiotemporal point sequence with low knowledge density to high-order semantic knowledge.Specifically,firstly,by analyzing the characteristics and constituent elements of ship activities,the ontology layer of ship activity knowledge map is designed based on the core idea of"process-event-behavior";Then,the track semantic information is extracted by Stop/Move model,and the ship emergencies are extracted by DMCNN model to complete the filling of instance layer;Finally,the above model and method are verified by constructing a prototype system.The results show that the ship activity knowledge map constructed in this paper can support the knowledge representation of ship routine activities and emergencies,and realize spatiotemporal activity query and backtracking,so as to achieve the effect of semantic enhancement,which has a certain application value.