Filipiak, D., Węcel, K., Stróżyna, M. et al. Extracting Maritime Traffic Networks from AIS Data Using Evolutionary Algorithm. Bus Inf Syst Eng 62, 435–450 (2020).

Skauen, A.N. Ship tracking results from state-of-the-art space-based AIS receiver systems for maritime surveillance. CEAS Space J 11, 301–316 (2019).

Chengkai Zhang, Junchi Bin, Wells Wang, Xiang Peng, Rui Wang, Richard Halldearn, Zheng Liu, AIS data driven general vessel destination prediction: A random forest based approach, Transportation Research Part C: Emerging Technologies, Volume 118, 2020, 102729, ISSN 0968-090X,

Kontopoulos, I., Varlamis, I., Tserpes, K. (2020). Uncovering Hidden Concepts from AIS Data: A Network Abstraction of Maritime Traffic for Anomaly Detection. In: Tserpes, K., Renso, C., Matwin, S. (eds) Multiple-Aspect Analysis of Semantic Trajectories. MASTER 2019. Lecture Notes in Computer Science, vol 11889. Springer, Cham.

Zhaojin Yan, Yijia Xiao, Liang Cheng, Rong He, Xiaoguang Ruan, Xiao Zhou, Manchun Li, Ran Bin. Exploring AIS data for intelligent maritime routes extraction. Applied Ocean Research. Volume 101. 2020. 102271. ISSN 0141-1187.

Liye Zhang, Qiang Meng, Tien Fang Fwa, Big AIS data based spatial-temporal analyses of ship traffic in Singapore port waters, Transportation Research Part E: Logistics and Transportation Review, Volume 129, 2019, Pages 287-304, ISSN 1366-5545,

Dong Yang, Lingxiao Wu, Shuaian Wang, Haiying Jia & Kevin X. Li (2019) How big data enriches maritime research – a critical review of Automatic Identification System (AIS) data applications, Transport Reviews, 39:6, 755-773, DOI: 10.1080/01441647.2019.1649315

Dobrkovic, A., Iacob, ME. & van Hillegersberg, J. Maritime pattern extraction and route reconstruction from incomplete AIS data. Int J Data Sci Anal 5, 111–136 (2018).

Mieczyńska, M., Czarnowski, I. K-means clustering for SAT-AIS data analysis. WMU J Marit Affairs 20, 377–400 (2021).

Andreas Tritsarolis, Yannis Kontoulis, Yannis Theodoridis, The Piraeus AIS dataset for large-scale maritime data analytics, Data in Brief, Volume 40, 2022, 107782, ISSN 2352-3409,

Marta Mieczyńska, Ireneusz Czarnowski, DBSCAN algorithm for AIS data reconstruction, Procedia Computer Science, Volume 192, 2021, Pages 2512-2521, ISSN 1877-0509,

Wang, Z.; Claramunt, C.; Wang, Y. Extracting Global Shipping Networks from Massive Historical Automatic Identification System Sensor Data: A Bottom-Up Approach. Sensors 2019, 19, 3363.

LaRock, T., Xu, M. & Eliassi-Rad, T. A path-based approach to analyzing the global liner shipping network. EPJ Data Sci. 11, 18 (2022).

Jing-Jing Pan, Yong-Feng Zhang, Bi Fan, Strengthening container shipping network connectivity during COVID-19: A graph theory approach, Ocean & Coastal Management, Volume 229, 2022, 106338, ISSN 0964-5691,

M. Le Tixerant, D. Le Guyader, F. Gourmelon, B. Queffelec, How can Automatic Identification System (AIS) data be used for maritime spatial planning?, Ocean & Coastal Management, Volume 166, 2018, Pages 18-30, ISSN 0964-5691,

Wells Wang, Junchi Bin, Amirhossein Zaji, Richard Halldearn, Fabien Guillaume, Eric Li, Zheng Liu, A multi-task learning-based framework for global maritime trajectory and destination prediction with AIS data, Maritime Transport Research, Volume 3, 2022, 100072, ISSN 2666-822X,