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Weka-STPM: A Software Architecture and Prototype for Semantic Trajectory Data Mining and Visualization

机译:Weka-STPM:用于语义轨迹数据挖掘和可视化的软件体系结构和原型

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摘要

Enormous quantities of trajectory data are collected from many sources, such as GPS devices and mobile phones, as sequences of spatio-temporal points. These data can be used in many application domains such as traffic management, urban planning, tourism, bird migration, and so on. Raw trajectory data, as generated by mobile devices have very little or no semantics, and in most applications a higher level of abstraction is needed to exploit these data for decision making. Although several different methods have been proposed so far for trajectory querying and mining, there are no software tools to help the end user with semantic trajectory data analysis. In this article we present a software architecture for semantic trajectory data mining as well as the first software prototype to enrich trajectory data with both semantic information and data mining. As a prototype we extend the Weka data mining toolkit with the module Weka-STPM, which is interoperable with databases constructed under OGC specifications. We tested Weka-STPM with real geographic databases, and trajectory data stored under the Postgresql/PostGIS DBMS.
机译:作为时空点序列,从许多来源(如GPS设备和移动电话)收集了大量的轨迹数据。这些数据可用于许多应用领域,例如交通管理,城市规划,旅游,鸟类迁徙等。由移动设备生成的原始轨迹数据几乎没有语义,甚至没有语义,在大多数应用中,需要更高级别的抽象来利用这些数据进行决策。尽管到目前为止已经提出了几种不同的方法来进行轨迹查询和挖掘,但是还没有软件工具可以帮助最终用户进行语义轨迹数据分析。在本文中,我们介绍了用于语义轨迹数据挖掘的软件体系结构,以及第一个使用语义信息和数据挖掘来丰富轨迹数据的软件原型。作为原型,我们使用模块Weka-STPM扩展了Weka数据挖掘工具包,该模块可与根据OGC规范构建的数据库互操作。我们使用真实的地理数据库以及存储在Postgresql / PostGIS DBMS下的轨迹数据对Weka-STPM进行了测试。

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