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    Sliding window based weighted periodic pattern mining over time series data 

    Rizvee, Redwan Ahmed; Shahin, Md Shahadat Hossain; Ahmed, Chowdhury Farhan; Leung, Carson K.; Deng, Deyu; Mai, Jiaxing Jason (ibai publishing, 2019-07)
    Sliding windows have been crucial in mining time series. Many existing studies focus on reconstruction of the underlying structure (e.g., suffix tree) for each new window. However, when the window size is large or when the ...
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    AI-based sensor information fusion for supporting deep supervised learning 

    Leung, Carson K.; Braun, Peter; Cuzzocrea, Alfredo (MDPI, 2019-03)
    In recent years, artificial intelligence (AI) and its subarea of deep learning have drawn the attention of many researchers. At the same time, advances in technologies enable the generation or collection of large amounts ...
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    WeFreS: weighted frequent subgraph mining in a single large graph 

    Ashraf, Nahian; Haque, Riddho Ridwanul; Islam, Md. Ashraful; Ahmed, Chowdhury Farhan; Leung, Carson K.; Mai, Jiaxing Jason; Wodi, Bryan H. (ibai publishing, 2019-07)
    Considering edge weights during frequent subgraph mining can help us discover more interesting and useful subgraph patterns when compared to its unweighted counterparts. Although some recent works have proposed weight ...
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    An effective and efficient technique for supporting privacy-preserving keyword-based search over encrypted data in clouds 

    Cuzzocrea, Alfredo; Leung, Carson K.; Wodi, Bryan H.; Sourav, S.; Fadda, Edoardo (Elsevier, 2020)
    Nowadays, cloud providers offer to their clients the possibility of storage of emails and files on the cloud server. To avoid privacy concerns, encryption should be applied to data. Unlike searching plaintext documents by ...
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    An efficient approach for mining weighted frequent patterns with dynamic weights 

    Dewan, Umama; Ahmed, Chowdhury Farhan; Leung, Carson K.; Rizvee, Redwan Ahmed; Deng, Deyu; Souza, Joglas (ibai publishing, 2019-07)
    Weighted frequent pattern (WFP) mining is considered to be more effective than traditional frequent pattern mining because of its consideration of different semantic significance (weights) of items. However, most existing ...
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    A combined deep-learning and transfer-learning approach for supporting social influence prediction 

    Cuzzocrea, Alfredo; Leung, Carson K.; Deng, Deyu; Mai, Jiaxing Jason; Jiang, Fan; Fadda, Edoardo (Elsevier, 2020)
    Social influence is a phenomenon describing the spread of opinions across the population. Nowadays, social influence analysis (SIA) has a great impact. For example, viral marketing and online content recommendation are ...
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    Self-supervised deep learning model for COVID-19 lung CT image segmentation highlighting putative causal relationship among age, underlying disease and COVID-19 

    Fung, Daryl L. X.; Liu, Qian; Zammit, Judah; Leung, Carson K.; Hu, Pingzhao (2021-07-26)
    Abstract Background Coronavirus disease 2019 (COVID-19) is very contagious. Cases appear faster than the available Polymerase Chain Reaction test kits in many countries. ...
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    Adaptive multiple imputations of missing values using the class center 

    Phiwhorm, Kritbodin; Saikaew, Charnnarong; Leung, Carson K.; Polpinit, Pattarawit; Saikaew, Kanda R. (2022-04-28)
    Abstract Big data has become a core technology to provide innovative solutions in many fields. However, the collected dataset for data analysis in various domains will contain missing values. Missing value ...
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    The effect of disease co-occurrence measurement on multimorbidity networks: a population-based study 

    Monchka, Barret A.; Leung, Carson K.; Nickel, Nathan C.; Lix, Lisa M. (2022-06-08)
    Abstract Background Network analysis, a technique for describing relationships, can provide insights into patterns of co-occurring chronic health conditions. The effect that ...
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    Semi-supervised COVID-19 CT image segmentation using deep generative models 

    Zammit, Judah; Fung, Daryl L. X.; Liu, Qian; Leung, Carson K.; Hu, Pingzhao (2022-08-17)
    Abstract Background A recurring problem in image segmentation is a lack of labelled data. This problem is especially acute in the segmentation of lung computed tomography (CT) ...
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    leung, carson k. (30)
    cuzzocrea, alfredo (15)jiang, fan (6)braun, peter (5)ahmed, chowdhury farhan (3)cameron, juan j. (3)deng, deyu (3)... View MoreSubjectdata mining (12)uncertain data (5)frequent patterns (4)database theory (3)extending database technology (3)knowledge discovery (3)knowledge discovery and data mining (3)... View MoreDate Issued2020 - 2022 (10)2011 - 2019 (20)

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