Blar i SINTEF Open på forfatter "Djenouri, Youcef"

Viser treff 1-20 av 45

    • Artificial intelligence of medical things for disease detection using ensemble deep learning and attention mechanism 

      Djenouri, Youcef; Belhadi, Asma; Yazidi, Anis; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      In this paper, we present a novel paradigm for disease detection. We build an artificial intelligence based system where various biomedical data are retrieved from distributed and homogeneous sensors. We use different deep ...

    • Cluster-based information retrieval using pattern mining 

      Djenouri, Youcef; Belhadi, Asma; Djenouri, Djamel; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2020)
      This paper addresses the problem of responding to user queries by fetching the most relevant object from a clustered set of objects. It addresses the common drawbacks of cluster-based approaches and targets fast, high-quality ...

    • A data-driven approach for twitter hashtag recommendation 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Cano, Alberto (Peer reviewed; Journal article, 2020)
      This paper addresses the hashtag recommendation problem using high average-utility pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for Hashtag Recommendation). It consists of two main stages. ...

    • A Data-Driven Approach for Twitter Hashtag Recommendation 

      Djenouri, Youcef; Asma, Belhadi; Chun-Wei Lin, Jerry; Alberto, Cano (Peer reviewed; Journal article, 2020)
      This paper addresses the hashtag recommendation problem using high average-utility pattern mining. We introduce a novel framework called PM-HRec (Pattern Mining for Hashtag Recommendation). It consists of two main stages. ...

    • Deep learning based decomposition for visual navigation in industrial platforms 

      Djenouri, Youcef; Hatleskog, Johan; Hjelmervik, Jon M.; Bjorne, Elias; Utstumo, Trygve; Mobarhan, Milad (Peer reviewed; Journal article, 2021)
      In the heavy asset industry, such as oil & gas, offshore personnel need to locate various equipment on the installation on a daily basis for inspection and maintenance purposes. However, locating equipment in such GPS ...

    • Deep learning based hashtag recommendation system for multimedia data 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This work aims to provide a novel hybrid architecture to suggest appropriate hashtags to a collection of orpheline tweets. The methodology starts with defining the collection of batches used in the convolutional neural ...

    • Deep learning for pedestrian collective behavior analysis in smart cities: A model of group trajectory outlier detection 

      Belhadi, Asma; Djenouri, Youcef; Srivastava, Gautam; Djenouri, Djamel; Lin, Jerry Chun-Wei; Fortino, Giancarlo (Peer reviewed; Journal article, 2021)
      This paper introduces a new model to identify collective abnormal human behaviors from large pedestrian data in smart cities. To accurately solve the problem, several algorithms have been proposed in this paper. These can ...

    • Deviation Point Curriculum Learning for Trajectory Outlier Detection in Cooperative Intelligent Transport Systems 

      Ahmed, Usman; Srivastava, Gautam; Djenouri, Youcef; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Cooperative Intelligent Transport Systems (C-ITS) are emerging in the field of transportation systems, which can be used to provide safety, sustainability, efficiency, communication and cooperation between vehicles, roadside ...

    • An edge-driven multi-agent optimization model for infectious disease detection 

      Djenouri, Youcef; Srivastava, Gautam; Yazidi, Anis; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2022)
      This research work introduces a new intelligent framework for infectious disease detection by exploring various emerging and intelligent paradigms. We propose new deep learning architectures such as entity embedding networks, ...

    • Efficient Chain Structure for High-Utility Sequential Pattern Mining 

      Lin, Jerry Chun-Wei; Li, Yuanfa; Fournier-Viger, Philippe; Djenouri, Youcef; Zhang, Ji (Peer reviewed; Journal article, 2020)
      High-utility sequential pattern mining (HUSPM) is an emerging topic in data mining, which considers both utility and sequence factors to derive the set of high-utility sequential patterns (HUSPs) from the quantitative ...

    • Emergent Deep Learning for Anomaly Detection in Internet of Everything 

      Djenouri, Youcef; Djenouri, Djamel; Belhadi, Asma; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This research presents a new generic deep learning framework for anomaly detection in the Internet of Everything (IoE). It combines decomposition methods, deep neural networks, and evolutionary computation to better detect ...

    • An evolutionary model to mine high expected utility patterns from uncertain databases 

      Ahmed, Usman; Lin, Jerry Chun-Wei; Srivastava, Gautam; Yasin, Rizwan; Djenouri, Youcef (Peer reviewed; Journal article, 2021)
      In recent decades, mobile or the Internet of Thing (IoT) devices are dramatically increasing in many domains and applications. Thus, a massive amount of data is generated and produced. Those collected data contain a large ...

    • Exploring Decomposition for Solving Pattern Mining Problems 

      Djenouri, Youcef; Lin, Jerry Chun-Wei; Nørvåg, Kjetil; Ramampiaro, Heri; Yu, Philip S. (Peer reviewed; Journal article, 2021)
      This article introduces a highly efficient pattern mining technique called Clustering-based Pattern Mining (CBPM). This technique discovers relevant patterns by studying the correlation between transactions in the transaction ...

    • Exploring Decomposition for Solving Pattern Mining Problems 

      Djenouri, Youcef; Lin, Jerry Chun-Wei; Nørvåg, Kjetil; Ramampiaro, Heri; Yu, Philip S. (Peer reviewed; Journal article, 2021)
      This article introduces a highly efficient pattern mining technique called Clustering-based Pattern Mining (CBPM). This technique discovers relevant patterns by studying the correlation between transactions in the transaction ...

    • Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Zhang, Chongsheng; Cano, Alberto (Peer reviewed; Journal article, 2020)
      Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social networks. This paper incorporates the pattern mining approaches to improve the accuracy of retrieving the relevant information ...

    • Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem 

      Djenouri, Youcef; Asma, Belhadi; Jerry, Chun-Wei Lin; Chongsheng, Zhang; Alberto, Cano (Peer reviewed; Journal article, 2020)
      Hashtag is an iconic feature to retrieve the hot topics of discussion on Twitter or other social networks. This paper incorporates the pattern mining approaches to improve the accuracy of retrieving the relevant information ...

    • Fast and accurate convolution neural network for detecting manufacturing data 

      Djenouri, Youcef; Srivastava, Gautam; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This article introduces a technique known as clustering with particle for object detection (CPOD) for use in smart factories. CPOD builds on regional-based methods to identify smart object data using outlier detection, ...

    • Fast and Accurate Deep Learning Framework for Secure Fault Diagnosis in the Industrial Internet of Things 

      Djenouri, Youcef; Belhadi, Asma; Srivastava, Gautam; Ghosh, Uttam; Chatterjee, Pushpita; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      This paper introduced a new deep learning framework for fault diagnosis in electrical power systems. The framework integrates the convolution neural network and different regression models to visually identify which faults ...

    • Fast and accurate group outlier detection for trajectory data 

      Djenouri, Youcef; Nørvåg, Kjetil; Ramampiaro, Heri; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2020)
      Previous approaches to solve the trajectory outlier detection problem exclusively examine single outliers. However, anomalies in trajectory data may often occur in groups. This paper introduces a new problem, group trajectory ...

    • 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 ...