文章基本信息

标题：Using Ontology Based Semantic Association Rule Mining in Location Based Services
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作者：Ali Mousavi ; Andrew Hunter ; Mohammad Akbari 等
期刊名称：International Journal of Data Mining & Knowledge Management Process
印刷版ISSN：2231-007X
电子版ISSN：2230-9608
出版年度：2016
卷号：6
期号：5
页码：1
DOI：10.5121/ijdkp.2016.6501
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Recently, GPS and mobile devices allowed collecting a huge amount of mobility data. Researchers fromdifferent communities have developed models and techniques for mobility analysis. But they mainly focusedon the geometric properties of trajectories and do not consider the semantic facet of moving objects. Thetechniques are good at extracting patterns, but they are hard to interpret in a specific application domain.This paper proposes a methodology to understand mobility data and semantically interpret trajectorypatterns. The process considers four different behavior types such as semantic, semantic and space,semantic and time, and semantic and space-time. Finally, a system prototype was developed to evaluate thebehavior models in different aspects using one of the location based services. The results showed thatapplying the semantic association rules could significantly reduce the number of available services andcustomize the services based on the rules.
关键词：Data mining; ontology; semantic; location based services; association rule mining; spatiotemporal data