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Including Content-Based Methods in Peer-Assessment of Open-Response Questions.

, , , , and . ICDM Workshops, page 273-279. IEEE Computer Society, (2015)

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Time series clustering based on the characterisation of segment typologies., , , , and . CoRR, (2018)MV-kWNN: A novel multivariate and multi-output weighted nearest neighbours algorithm for big data time series forecasting., , , and . Neurocomputing, (2019)Scatter search-based identification of local patterns with positive and negative correlations in gene expression data., , and . Appl. Soft Comput., (2015)Obtaining optimal quality measures for quantitative association rules., , , and . Neurocomputing, (2016)A novel methodology to predict urban traffic congestion with ensemble learning., , , and . Soft Comput., 20 (11): 4205-4216 (2016)A new Apache Spark-based framework for big data streaming forecasting in IoT networks., , , and . J. Supercomput., 79 (10): 11078-11100 (July 2023)A novel distributed forecasting method based on information fusion and incremental learning for streaming time series., , , and . Inf. Fusion, (July 2023)Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks., , , and . CAEPIA, volume 12882 of Lecture Notes in Computer Science, page 216-225. Springer, (2021)Deep Learning for Big Data Time Series Forecasting Applied to Solar Power., , , , and . SOCO-CISIS-ICEUTE, volume 771 of Advances in Intelligent Systems and Computing, page 123-133. Springer, (2018)Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering., , , , , , , and . SOCO, volume 1268 of Advances in Intelligent Systems and Computing, page 226-236. Springer, (2020)