Blar i Institutt for datateknologi, elektroteknologi og realfag på emneord "data mining"

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    • A Survey on Urban Traffic Anomalies Detection Algorithms 

      Djenouri, Youcef; Belhadi, Asma; Lin, Chun Wei; Djenouri, Djamel; Cano, Alberto (Journal article; Peer reviewed, 2019)
      This paper reviews the use of outlier detection approaches in urban traffic analysis. We divide existing solutions into two main categories: flow outlier detection and trajectory outlier detection. The first category groups ...

    • 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 ...

    • 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 ...

    • A Practical Methodology for Anonymization of Structured Health Data 

      Aminifar, Amin; Lamo, Yngve; Pun, Ka I; Rabbi, Fazle (Peer reviewed; Journal article, 2019)
      Hospitals, as data custodians, have the need to share a version of the data in hand with external research institutes for analysis purposes. For preserving the privacy of the patients, anonymization methods are employed ...

    • Space-time series clustering: Algorithms, taxonomy, and case study on urban smart cities 

      Belhadi, Asma; Djenouri, Youcef; Nørvåg, Kjetil; Ramampiaro, Heri; Masseglia, Florent; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2020)
      This paper provides a short overview of space–time series clustering, which can be generally grouped into three main categories such as: hierarchical, partitioning-based, and overlapping clustering. The first hierarchical ...