作者
Yu Zheng
发表日期
2015/5/12
来源
ACM Transactions on Intelligent Systems and Technology (TIST)
卷号
6
期号
3
页码范围
1-41
出版商
ACM
简介
The advances in location-acquisition and mobile computing techniques have generated massive spatial trajectory data, which represent the mobility of a diversity of moving objects, such as people, vehicles, and animals. Many techniques have been proposed for processing, managing, and mining trajectory data in the past decade, fostering a broad range of applications. In this article, we conduct a systematic survey on the major research into trajectory data mining, providing a panorama of the field as well as the scope of its research topics. Following a road map from the derivation of trajectory data, to trajectory data preprocessing, to trajectory data management, and to a variety of mining tasks (such as trajectory pattern mining, outlier detection, and trajectory classification), the survey explores the connections, correlations, and differences among these existing techniques. This survey also introduces the methods …
引用总数
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学术搜索中的文章
Y Zheng - ACM Transactions on Intelligent Systems and …, 2015