• 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 ...
    • Adapted k-Nearest Neighbors for Detecting Anomalies on Spatio-Temporal Traffic Flow 

      Djenouri, Youcef; Belhadi, Asma; Lin, Chun Wei; Djenouri, Djamel; Cano, Alberto (Journal article; Peer reviewed, 2019)
      Outlier detection is an extensive research area, which has been intensively studied in several domains such as biological sciences, medical diagnosis, surveillance, and traffic anomaly detection. This paper explores advances ...
    • 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 ...
    • 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 ...
    • 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 (Journal article; Peer reviewed, 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 ...