Abstract
Taxi is usually considered as the probe of roads in a city. A large amount of taxi GPS mobility data is able to reflect the human mobility and city traffic. The data is described in spatial and temporal form, from which more information can be mined. One kind of the information is related to the basic statistics of the taxi, such as the taxi id, average/min/max speed, travel distance, load or not etc. Other information such as the taxi’s trajectory or regions of interest in the city can also be obtained. In this paper, we introduce a TaxiCluster to visualize and analyze the taxi data. A procedure on the raw taxi trajectories is introduced in the TaxiCluster.
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Xie, M., Zhao, Q. (2017). TaxiCluster: A Visualization Platform on Clustering Algorithms for Taxi Trajectories. In: Song, S., Renz, M., Moon, YS. (eds) Web and Big Data. APWeb-WAIM 2017. Lecture Notes in Computer Science(), vol 10612. Springer, Cham. https://doi.org/10.1007/978-3-319-69781-9_14
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DOI: https://doi.org/10.1007/978-3-319-69781-9_14
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