• Applying temporal dependence to detect changes in streaming data 

      Duong, Quang-Huy; Ramampiaro, Heri; Nørvåg, Kjetil (Journal article; Peer reviewed, 2018)
      Detection of changes in streaming data is an important mining task, with a wide range of real-life ap- plications. Numerous algorithms have been proposed to efficiently detect changes in streaming data. However, the ...
    • Benchmarks for machine learning in depression discrimination using electroencephalography signals 

      Seal, Ayan; Bajpai, Rishabh; Karnati, Mohan; Agnihotri, Jagriti; Yazidi, Anis; Herrera-Viedma, Enrique; Krejcar, Ondrej (Journal article; Peer reviewed, 2022)
      Diagnosis of depression using electroencephalography (EEG) is an emerging field of study. When mental health facilities are unavailable, the use of EEG as an objective measure for depression management at an individual ...
    • Effective hate-speech detection in Twitter data using recurrent neural networks 

      Pitsilis, Georgios; Ramampiaro, Heri; Langseth, Helge (Journal article; Peer reviewed, 2018)
      This paper addresses the important problem of discerning hateful content in social media. We propose a detection scheme that is an ensemble of Recurrent Neural Network (RNN) classifiers, and it incorporates various features ...
    • Enhancing E-Learning Systems with Personalized Recommendation Based on Collaborative Tagging Techniques 

      Klašnja-MIlićević, Aleksandra; Ivanović, Mirjana; Vesin, Boban; Budimac, Zoran (Peer reviewed; Journal article, 2017)
      Personalization of the e-learning systems according to the learner’s needs and knowledge level presents the key element in a learning process. E-learning systems with personalized recommendations should adapt the learning ...
    • A general-purpose distributed pattern mining system 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Cano, Alberto (Peer reviewed; Journal article, 2020)
      This paper explores five pattern mining problems and proposes a new distributed framework called DT-DPM: Decomposition Transaction for Distributed Pattern Mining. DT-DPM addresses the limitations of the existing pattern ...
    • Persistence Initialization: a novel adaptation of the Transformer architecture for time series forecasting 

      Haugsdal, Espen; Aune, Erlend; Ruocco, Massimiliano (Peer reviewed; Journal article, 2023)
      Time series forecasting is an important problem, with many real world applications. Transformer models have been successfully applied to natural language processing tasks, but have received relatively little attention for ...
    • Using extended siamese networks to provide decision support in aquaculture operations 

      Mathisen, Bjørn Magnus; Bach, Kerstin; Aamodt, Agnar (Peer reviewed; Journal article, 2021)
      Aquaculture as an industry is quickly expanding. As a result, new aquaculture sites are being established at more exposed locations previously deemed unfit because they are more difficult and resource demanding to safely ...