• 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 ...
    • 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 ...
    • Adaptive Systems for Internet-Delivered Psychological Treatments 

      Mukhiya, Suresh Kumar; Wake, Jo Dugstad; Inal, Yavuz; Lamo, Yngve (Peer reviewed; Journal article, 2020)
      Internet-Delivered Psychological Treatments (IDPT) are based on evidence-based psychological treatment models adjusted for interaction through the Internet. The use of Internet technologies has the potential to increase ...
    • An Effective Approach for Obtaining a Group Trading Strategy Portfolio Using Grouping Genetic Algorithm 

      Chen, Chun-Hao; Chen, Yu-Hsuan; Lin, Chun Wei; Wu, Mu-En (Journal article; Peer reviewed, 2019)
      To determine an appropriate trading time for buying or selling stocks is always a difficult task. The common way to deal with it is using trading strategies formed by technical or fundamental indicators. Lots of approaches ...
    • A Bitmap Approach for Mining Erasable Itemsets 

      Hong, Tzung-Pei; Huang, Wei-Ming; Lan, Guo-Cheng; Chiang, Ming-Chao; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Erasable-itemset mining is a valuable method of pattern extraction for helping the manager of a factory analyze production planning. The erasable itemsets derived can be considered important production information regarding ...
    • A data-driven approach for twitter hashtag recommendation 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Cano, Alberto (Journal article; Peer reviewed, 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. ...
    • “Digital Twins” for Highly Customized Electronic Devices – Case Study on a Rework Operation 

      Cupek, Rafal; Drewniak, Marek; Ziebinski, Adam; Fojcik, Marcin (Peer reviewed; Journal article, 2019)
      The ongoing changes in manufacturing require that new information models for industrial computer systems be developed and applied. This paper describes a concept for the material model as a “digital twin” for producing ...
    • An Effective Approach for the Diverse Group Stock Portfolio Optimization Using Grouping Genetic Algorithm 

      Chen, Chung-Hao; Lu, Cheng-Yu; Hong, Tzung-Pei; Lin, Chun Wei; Gaeta, Matteo (Peer reviewed; Journal article, 2019)
      Finding useful portfolios that could be a portfolio of trading strategy or a stock portfolio from financial datasets is always an attractive research topic due to the nature of financial markets. Because investors always ...
    • 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 ...
    • Efficient Method for Mining High Utility Occupancy Patterns Based on Indexed List Structure 

      Kim, Hyeonmo; Ryu, Taewoong; Lee, Chanhee; Kim, Sinyoung; Vo, Bay; Lin, Jerry Chun-Wei; Yun, Unil (Peer reviewed; Journal article, 2023)
      High utility pattern mining has been proposed to improve the traditional support-based pattern mining methods that process binary databases. High utility patterns are discovered by effectively considering the quantity and ...
    • Enhancing Security of Health Information Using Modular Encryption Standard in Mobile Cloud Computing 

      Shabbir, Maryam; Shabbir, Ayesha; Iwendi, Celestine; Javed, Abdul Rehman; Rizwan, Muhammad; Herencsar, Norbert; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2021)
      Despite the numerous and noticeable inherited gains of Mobile Cloud Computing (MCC) in healthcare, its growth is being hindered by privacy and security challenges. Such issues require the utmost urgent attention to realize ...
    • Exploring Pattern Mining Algorithms for Hashtag Retrieval Problem 

      Belhadi, Asma; Djenouri, Youcef; Lin, Jerry Chun-Wei; Zhang, Chongsheng; Cano, Alberto (Journal article; Peer reviewed, 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 ...
    • Extremely Randomized Trees With Privacy Preservation for Distributed Structured Health Data 

      Aminifar, Amin; Matin, Shokri; Rabbi, Fazle; Pun, Violet Ka I; Lamo, Yngve (Peer reviewed; Journal article, 2022)
      Artificial intelligence and machine learning have recently attracted considerable attention in the healthcare domain. The data used by machine learning algorithms in healthcare applications is often distributed over multiple ...
    • Incrementally Updating the Discovered High Average-Utility Patterns With the Pre-Large Concept 

      Wu, Jimmy Ming-Tai; Teng, Qian; Lin, Jerry Chun-Wei; Cheng, Chien-Fu (Journal article; Peer reviewed, 2020)
      High average-utility itemset mining (HAUIM) is an extension of high-utility itemset mining (HUIM), which provides a reliable measure to reveal utility patterns by considering the length of the mined pattern. Some research ...
    • 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 ...
    • Multi-Network Vulnerability Causal Model for Infrastructure Co-Resilience 

      Konila Sriram, Lalitha Madhavi; Ulak, Mehmet Baran; Ozguven, Eren Erman; Arghandeh, Reza (Journal article; Peer reviewed, 2019)
      Resilience is mostly considered as a single-dimension attribute of a system. Most of the recent works on resilience treat it as a single-dimension attribute of a system or study the different dimensions of the resilience ...
    • Using Tree Structure to Mine High Temporal Fuzzy Utility Itemsets 

      Hong, Tzung-Pei; Lin, Cheng-Yu; Huang, Wei-Ming; Li, Katherine Shu-Min; Wang, Leon Shyue-Liang; Lin, Jerry Chun-Wei (Journal article; Peer reviewed, 2020)
      Data mining is a critical technology for extracting valuable knowledge from databases. It has been used in many fields, like retail, finance, biology, etc. In computational intelligence, fuzzy logic has been applied in ...
    • Visualization of generic utility of sequential patterns 

      Wiktorski, Tomasz; Królak, Aleksandra; Rosińska, Karolina; Strumillo, Pawel; Lin, Jerry Chun-Wei (Peer reviewed; Journal article, 2020)
      Most of the literature on utility pattern mining (UPM) assumes that the particular patterns' utility in known in advance. Concurrently, in frequent pattern mining (FPM) it is assumed that all patterns take the same value. ...
    • When the Decomposition Meets the Constraint Satisfaction Problem 

      Djenouri, Youcef; Djenouri, Djamel; Habbas, Zineb; Lin, Jerry Chun-Wei; Michalak, Tomasz P.; Cano, Alberto (Peer reviewed; Journal article, 2020)
      This paper explores the joint use of decomposition methods and parallel computing for solving constraint satisfaction problems and introduces a framework called Parallel Decomposition for Constraint Satisfaction Problems ...