An ontology-based framework to support performance monitoring in public transport systems

Managers of public transport systems have been facing for years the strategic challenge of maintaining high quality of transport services to improve the mobility of citizens, while reducing costs and ensuring safety and low environmental impact. A well-established way to evaluate the performance achieved by the system or by specific activities is to monitor Key Performance Indicators (KPI). However, existing management systems, which refer to flexible yet large and complex data models, provide a limited support to define and select relevant KPIs for the objectives at hand, and even the identification of whether and how the data model is capable to achieve a certain informative need is a critical and time-consuming task. This work is aimed to propose a framework to ease the development of a monitoring system in the public transport domain. The approach is based on the ontological representation of all the knowledge regarding indicators and their formulas, business objectives, dimension analysis and their relation with the Transmodel, the European reference data model for public transport information systems. On its top, a reasoning framework provides logic functionalities to interactively support designers in a set of common design tasks: the choice of the most suitable indicators for the performance monitoring needs at hand, the definition of new indicators and the identification of the minimal set of Transmodel modules needed to calculate them. A case study is included to discuss these applications, while an evaluation shows the feasibility of the approach.     

基于Ontology和Jena的个性化E-Learning系统研究

介绍了E-Learning系统的若干关键技术,阐述了如何利用本体方法建立一种面向语义的非结构化教学资源的表示机制以及利用Jena推理机制进行非结构化教学信息的语义访问和个性化学习指导,在此基础上,实现了一个基于Ontology和Jena推理机制的个性化E-Learning系统模型,并对E-Learning系统未来的发展进行了展望.     

一种采用SOM架构的信息过滤系统语义扩展方法研究

论述一种基于自组地图(SOMSelf-Organizing Maps)架构的信息过滤系统语义扩展方法,利用系统本体对海量文本信息系统特征词之间的关联关系进行建模,计算文本信息的特征向量作为自组地图的输入,为用户实现一种直观的信息导航视图.相应实验结果表明,利用本体系统改善特征词权重的计算有效提高文本信息特征向量的分类和标示精度,减少系统的语义重复性,同时自组地图为用户提供的结果信息可以帮助其更为直观精确的定位到需求信息.     

An ontological model to support communications of situation-aware vehicles

In an Intelligent Transport System (ITS) environment, the communication component is of great importance to support interactions between vehicles and roadside infrastructure. Previous studies have focused on the physical capability and capacity of the communication technologies, but the equally important development of suitable and efficient semantic content for transmission received notably less attention. Ontology is one promising approach for context modelling in ubiquitous computing environments, and in the transport domain it can be used both for context modelling and semantic contents for vehicular communications. This paper explores the development of an ontological model implementing relative geo-semantic information messages to support vehicle-to-vehicle communications. The proposed ontology model contains classes, objects, their properties/relations as well as some functions and query templates to represent and update the information of dynamic vehicles, inter-vehicle interactions and behaviour. This model was developed through a scenario enabling the evaluation of traffic conflict resolution approaches, by implementing a set of decision-making processes for intelligent vehicles. Given the scope of the proposed ontology modelling, it shows how vehicular communications can be used to update each vehicle’s context model. This work can be easily extended for more complex interactions among vehicles and the infrastructure.