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Leveraging User Mobility and Mobile App Services Behavior for Optimal Edge Resource Utilization., , , , and . COINS, page 7-12. ACM, (2019)Comparing Methods for Twitter Sentiment Analysis, , , and . Proceedings of the 6th International Conference on Knowledge Discovery and Information Retrieval - KDIR 2014, (2014)Comparing Methods for Twitter Sentiment Analysis., , , and . KDIR, page 225-232. SciTePress, (2014)Streamlining XR Application Deployment with a Localized Docker Registry at the Edge., , , , , , , , , and . ESOCC, volume 14183 of Lecture Notes in Computer Science, page 188-202. Springer, (2023)Sentiment Analysis using Word-Graphs., , , , and . WIMS, page 22:1-22:9. ACM, (2016)Semi-supervised trajectory classification using convolutional auto-encoders., , , and . HANIMOB@SIGSPATIAL, page 27-32. ACM, (2021)GNOSIS: Proactive Image Placement Using Graph Neural Networks & Deep Reinforcement Learning., , , , , , and . CLOUD, page 120-128. IEEE, (2023)Implementation of a decision support system for prediction of the total soluble solids of industrial tomato using machine learning models., , , , , , , and . Comput. Electron. Agric., (2022)Towards a Distributed Storage Framework for Edge Computing Infrastructures., , , and . FRAME@HPDC, page 9-14. ACM, (2022)Using LSTM Neural Networks as Resource Utilization Predictors: The Case of Training Deep Learning Models on the Edge., , , , and . GECON, volume 12441 of Lecture Notes in Computer Science, page 67-74. Springer, (2020)