STMaker

Author:

Su Han1,Zheng Kai1,Zeng Kai2,Huang Jiamin3,Zhou Xiaofang1

Affiliation:

1. University of Queensland, Brisbane, Australia

2. University California, Los Angeles, Los Angeles

3. Nanjing University, Nanjing, China

Abstract

Widely adoption of GPS-enabled devices generates large amounts of trajectories every day. The raw trajectory data describes the movement history of moving objects by a sequence of < longitude, latitude, time-stamp > triples, which are nonintuitive for human to perceive the prominent features of the trajectory, such as where and how the moving object travels. In this demo, we present the STMaker system to help users make sense of individual trajectories. Given a trajectory, STMaker can automatically extract the significant semantic behavior of the trajectory, and summarize the behavior by a short human-readable text. In this paper, we first introduce the phrases of generating trajectory summarizations, and then show several real trajectory summarization cases.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 25 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Similarity Measurement of Trajectory Data Stream Based on Incremental DBSCAN;2023 International Conference on Algorithms, Computing and Data Processing (ACDP);2023-06-23

2. TSummary: A Traffic Summarization System Using Semantic Words;Database Systems for Advanced Applications. DASFAA 2022 International Workshops;2022

3. Time Synchronized Velocity Error for Trajectory Compression;Computer Modeling in Engineering & Sciences;2022

4. Review and classification of trajectory summarisation algorithms: From compression to segmentation;International Journal of Distributed Sensor Networks;2021-10

5. Mobility Driven Cloud-Fog-Edge Framework for Location-Aware Services: A Comprehensive Review;Mobile Edge Computing;2021

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