Blar i HVL Open på forfatter "Fournier-Viger, Philippe"

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    • A Sanitization Approach to Secure Shared Data in an IoT Environment 

      Lin, Chun Wei; Wu, Jimmy Ming-Tai; Fournier-Viger, Philippe; Djenouri, Youcef; Chen, Chun-Hao; Zhang, Yuyu (Journal article; Peer reviewed, 2019)
      Internet of Things (IoT) supports high flexibility and convenience in several applications because the IoT devices continuously transfer, share, and exchange data without human intervention. During shared or exchanged ...

    • BILU-NEMH: A BILU neural-encoded mention hypergraph for mention extraction 

      Lin, Chun Wei; Shao, Yinan; Fournier-Viger, Philippe; Hamido, Fujita (Peer reviewed; Journal article, 2019)
      The natural language processing (NLP) denotes a technique used to process data such as text and speech. Some of the fundamental research in NLP includes the named entity recognition, which recognizes the named entities ...

    • Discovering Periodic Itemsets using Novel Periodicity Measures 

      Fournier-Viger, Philippe; Yang, Peng; Lin, Chun Wei; Duong, Quang-Huy; Dam, Thu-Lan; Frnda, Jaroslav; Sevcik, Lukas; Voznak, Miroslav (Journal article; Peer reviewed, 2019)
      Discovering periodic patterns in a customer transaction database is the task of identifying itemsets (sets of items or values) that periodically appear in a sequence of transactions. Numerous methods can identify ...

    • 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 ...

    • FHUQI-Miner: Fast high utility quantitative itemset mining 

      Nouioua, Mourad; Fournier-Viger, Philippe; Wu, Cheng-Wei; Lin, Jerry Chun-Wei; Gan, Wensheng (Peer reviewed; Journal article, 2021)
      High utility itemset mining is a popular pattern mining task, which aims at revealing all sets of items that yield a high profit in a transaction database. Although this task is useful to understand customer behavior, an ...

    • Maintenance of discovered high average-utility itemsets in dynamic databases 

      Zhang, Binbin; Lin, Jerry Chun-Wei; Shao, Yinan; Fournier-Viger, Philippe; Djenouri, Youcef (Journal article; Peer reviewed, 2018)
      High-utility itemset mining (HUIM) is an extension of traditional frequent itemset mining, which considers both quantities and unit profits of items in a database to reveal highly profitable itemsets regardless of their ...

    • Mining Productive Itemsets in Dynamic Databases 

      Li, Xiang; Li, Jiaxuan; Fournier-Viger, Philippe; Nawaz, M. Saqib; Yao, Jie; Lin, Jerry Chun-Wei (Journal article; Peer reviewed, 2020)
      Discovering frequent itemsets is a data analysis task used in numerous domains. It consists of finding sets of items (itemsets) that frequently appear in a set of database records (also called transactions). Though discovering ...

    • Mining Profitable and Concise Patterns in Large-Scale Internet of Things Environments 

      Lin, Jerry Chun-Wei; Djenouri, Youcef; Srivastava, Gautam; Fournier-Viger, Philippe (Peer reviewed; Journal article, 2021)
      In recent years, HUIM (or a.k.a. high-utility itemset mining) can be seen as investigated in an extensive manner and studied in many applications especially in basket-market analysis and its relevant applications. Since ...

    • QoS to QoE Mapping Function for Iptv Quality Assessement Based on Kohonen Map: A Pilot Study 

      Frnda, Jaroslav; Durica, Marek; Savrasovs, Mihail; Fournier-Viger, Philippe; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2020)
      This paper deals with an analysis of Kohonen map usage possibility for real-time evaluation of end-user video quality perception. The Quality of Service framework (QoS) describes how the network impairments (network ...

    • The density-based clustering method for privacy-preserving data mining 

      Wu, Jimmy Ming-Tai; Lin, Chun Wei; Fournier-Viger, Philippe; Djenouri, Youcef; Chen, Chun-Hao; Li, Zhongcui (Journal article; Peer reviewed, 2019)
      Privacy-preserving data mining has become an interesting and emerging issue in recent years since it can, not only hide the sensitive information but still mine the meaningful knowledge at the same time. Since privacy-preserving ...