|
|
|
|
|
Lei Zhou, Weiye Xiao, Chen Wang, Haoran Wang
Pág. 143 - 161
Human mobility datasets, such as traffic flow data, reveal the connections between urban spaces. A novel framework is proposed to explore the spatial association between urban commercial and residential spaces via consumption travel flows in Shanghai. A ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Aidi Li, Zhijie Xu, Jianqin Zhang, Taizeng Li, Xinyue Cheng and Chaonan Hu
With the rapid growth of trajectory big data, there is a need for more efficient methods to extract, analyze, and visualize these data. However, existing research on trajectory big data visualization mainly focuses on displaying trajectories for a specif...
ver más
|
|
|
|
|
|
|
|
|
|
|
Jianing Ding, Xin Jin and Zhiheng Li
The Time-Period-Based Most Frequent Path (TPMFP) problem has been a hot topic in traffic studies for many years. The TPMFP problem involves finding the most frequent path between two locations by observing the travelling behaviors of drivers in a specifi...
ver más
|
|
|
|
|
|
|
|
|
|
|
Iori Sasaki, Masatoshi Arikawa, Min Lu and Ryo Sato
This paper proposes a model-less feedback system driven by tourist tracking data that are automatically collected through mobile applications to visualize the gap between geomedia recommendations and the actual routes selected by tourists. High-frequency...
ver más
|
|
|
|
|
|
|
|
|
|
|
Shuqiang Xu, Qunying Huang and Zhiqiang Zou
Location-based social networks (LBSN) allow users to socialize with friends by sharing their daily life experiences online. In particular, a large amount of check-ins data generated by LBSNs capture the visit locations of users and open a new line of res...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yulong Bai, Guolian Li, Tianxiu Lu, Yadong Wu, Weihan Zhang and Yidan Feng
Most existing road network matching algorithms are designed based on previous rules and do not fully utilize the potential of big data and historical tracks. To solve this problem, we introduce a new road network matching algorithm based on deep learning...
ver más
|
|
|
|
|
|
|
|
|
|
|
Kunlong Hong, Hongguang Wang and Bingbing Yuan
For the surface defects inspection task, operators need to check the defect in local detail images by specifying the location, which only the global 3D model reconstruction can?t satisfy. We explore how to address multi-type (original image, semantic ima...
ver más
|
|
|
|
|
|
|
|
|
|
|
Zhixin Yao, Jianqin Zhang, Taizeng Li and Ying Ding
Trajectory big data is suitable for distributed storage retrieval due to its fast update speed and huge data volume, but currently there are problems such as hot data writing, storage skew, high I/O overhead and slow retrieval speed. In order to solve th...
ver más
|
|
|
|
|
|
|
|
|
|
|
Weiwei Jiang and Jiayun Luo
Big data have been used widely in many areas, including the transportation industry. Using various data sources, traffic states can be well estimated and further predicted to improve the overall operation efficiency. Combined with this trend, this study ...
ver más
|
|
|
|
|
|
|
|
|
|
|
Yusi Liu, Xiang Gao, Disheng Yi, Heping Jiang, Yuxin Zhao, Jun Xu and Jing Zhang
Massive taxi trajectory data can be easily obtained in the era of big data, which is helpful to reveal the spatiotemporal information of human travel behavior but neglects activity semantics. The activity semantics reflect people?s daily activities and t...
ver más
|
|
|
|
|
|