Transportation mode inference from anonymized and aggregated mobile phone call detail records

H Wang, F Calabrese, G Di Lorenzo… - 13th International IEEE …, 2010 - ieeexplore.ieee.org
Transportation mode inference is an important research direction and has many
applications. Existing methods are usually based on fine-grained sampling-collecting …

Towards mobile intelligence: Learning from GPS history data for collaborative recommendation

VW Zheng, Y Zheng, X Xie, Q Yang - Artificial Intelligence, 2012 - Elsevier
With the increasing popularity of location-based services, we have accumulated a lot of
location data on the Web. In this paper, we are interested in answering two popular location …

Deriving personal trip data from GPS data: A literature review on the existing methodologies

L Gong, T Morikawa, T Yamamoto, H Sato - Procedia-Social and …, 2014 - Elsevier
GPS technology was used in person trip (PT) survey since mid-1990, and this technology
achieved its popularity because of the improvement of accuracy and portability of GPS …

Learning transportation modes from smartphone sensors based on deep neural network

SH Fang, YX Fei, Z Xu, Y Tsao - IEEE Sensors Journal, 2017 - ieeexplore.ieee.org
In recent years, the importance of user information has increased rapidly for context-aware
applications. This paper proposes a deep learning mechanism to identify the transportation …

Finding similar users using category-based location history

X Xiao, Y Zheng, Q Luo, X Xie - Proceedings of the 18th SIGSPATIAL …, 2010 - dl.acm.org
In this paper, we aim to estimate the similarity between users according to their GPS
trajectories. Our approach first models a user's GPS trajectories with a semantic location …

Mining GPS data for mobility patterns: A survey

M Lin, WJ Hsu - Pervasive and mobile computing, 2014 - Elsevier
With the help of various positioning tools, individuals' mobility behaviors are being
continuously captured from mobile phones, wireless networking devices and GPS …

On distributed fuzzy decision trees for big data

A Segatori, F Marcelloni… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Fuzzy decision trees (FDTs) have shown to be an effective solution in the framework of fuzzy
classification. The approaches proposed so far to FDT learning, however, have generally …

TrajFormer: Efficient trajectory classification with transformers

Y Liang, K Ouyang, Y Wang, X Liu, H Chen… - Proceedings of the 31st …, 2022 - dl.acm.org
Transformers have been an efficient alternative to recurrent neural networks in many
sequential learning tasks. When adapting transformers to modeling trajectories, we …

[HTML][HTML] Explaining the power-law distribution of human mobility through transportationmodality decomposition

K Zhao, M Musolesi, P Hui, W Rao, S Tarkoma - Scientific reports, 2015 - nature.com
Human mobility has been empirically observed to exhibit Lévy flightcharacteristics and
behaviour with power-law distributed jump size. The fundamentalmechanisms behind this …

Transportation mode-based segmentation and classification of movement trajectories

F Biljecki, H Ledoux… - International Journal of …, 2013 - Taylor & Francis
The knowledge of the transportation mode used by humans (eg bicycle, on foot, car and
train) is critical for travel behaviour research, transport planning and traffic management …