Performance Profiling of Operating Modes via Multi-view Analysis Using Non-negative Matrix Factorisation
Dhont, M , Tsiporkova, E & Boeva, V 2022, Performance Profiling of Operating Modes via Multi-view Analysis Using Non-negative Matrix Factorisation . in Studies in Big Data. Studies in Big Data, vol. 106, Springer, pp. 289-316.
Dynamic Imputation Methodology for Multi-source Streaming Mobility Data
Dhont, M , Tsiporkova, E & González-Deleito, N 2022, Dynamic Imputation Methodology for Multi-source Streaming Mobility Data . in Y Bie, BX Qu, RJ Howlett & LC Jain (eds), Smart Transportation Systems 2022. Smart Innovation, Systems and Technologies, vol. 304 SIST, Springer, pp. 184-198.
Advanced exploration of wind fleet data through operating mode labelling
Dhont, M , Verbeke, R, Droutsas, C, Boeva, V, Verbeke, M, Murgia, A & Tsiporkova, E 2021, Advanced exploration of wind fleet data through operating mode labelling . in Proceedings 5th RESRB 2020: Renewable Energy Sources – Research and Business. vol. 5, Wojciech Budzianowski Consulting Services, pp. 1-4, Renewable Energy Sources – Research and Business 2020, Brussels, Belgium, 7/09/20 .
Deriving Spatio-temporal Trajectory Fingerprints from Mobility Data using Non-Negative Matrix Factorisation
Dhont, M , Tsiporkova, E & González-Deleito, N 2021, Deriving Spatio-temporal Trajectory Fingerprints from Mobility Data using Non-Negative Matrix Factorisation . in B Xue, M Pechenizkiy & YS Koh (eds), 2021 International Conference on Data Mining Workshops (ICDMW). IEEE International Conference on Data Mining Workshops, ICDMW, vol. 2021-December, IEEE, Auckland, New Zealand, pp. 750-759, 21st IEEE International Conference on Data Mining, Auckland, New Zealand, 7/12/21 .
Visual Analytics for Extracting Trends from Spatio-temporal Data
Dhont, M , Tsiporkova, E, Tourwé, T & González-Deleito, N 2020, Visual Analytics for Extracting Trends from Spatio-temporal Data . in International Workshop on Advanced Analytics and Learning on Temporal Data: AALTD 2020: Advanced Analytics and Learning on Temporal Data. Lecture Notes in Computer Science , vol. 12588, Springer, pp. 122-137, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020, Ghent, Belgium, 14/09/20 .
Layered Integration Approach for Multi-view Analysis of Temporal Data
Dhont, M , Tsiporkova, E & Boeva, V 2020, Layered Integration Approach for Multi-view Analysis of Temporal Data . in V Lemaire, S Malinowski, A Bagnall, T Guyet, R Tavenard & G Ifrim (eds), Advanced Analytics and Learning on Temporal Data - 5th ECML PKDD Workshop, AALTD 2020, Revised Selected Papers: AALTD 2020: Advanced Analytics and Learning on Temporal Data. vol. 12588, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12588 LNAI, Springer, pp. 138-154, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2020, Ghent, Belgium, 14/09/20 .