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  • Open Access


    Using Link-Based Consensus Clustering for Mixed-Type Data Analysis

    Tossapon Boongoen, Natthakan Iam-On*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1993-2011, 2022, DOI:10.32604/cmc.2022.019776

    Abstract A mix between numerical and nominal data types commonly presents many modern-age data collections. Examples of these include banking data, sales history and healthcare records, where both continuous attributes like age and nominal ones like blood type are exploited to characterize account details, business transactions or individuals. However, only a few standard clustering techniques and consensus clustering methods are provided to examine such a data thus far. Given this insight, the paper introduces novel extensions of link-based cluster ensemble, and that are accurate for analyzing mixed-type data. They promote diversity within an ensemble through different initializations of the k-prototypes algorithm… More >

  • Open Access


    A Link Analysis Algorithm for Identification of Key Hidden Services

    Abdullah Alharbi1, Mohd Faizan2, Wael Alosaimi1, Hashem Alyami3, Mohd Nadeem2, Suhel Ahmad Khan4, Alka Agrawal2, Raees Ahmad Khan2,*

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 877-886, 2021, DOI:10.32604/cmc.2021.016887

    Abstract The Tor dark web network has been reported to provide a breeding ground for criminals and fraudsters who are exploiting the vulnerabilities in the network to carry out illicit and unethical activities. The network has unfortunately become a means to perpetuate crimes like illegal drugs and firearm trafficking, violence and terrorist activities among others. The government and law enforcement agencies are working relentlessly to control the misuse of Tor network. This is a study in the similar league, with an attempt to suggest a link-based ranking technique to rank and identify the influential hidden services in the Tor dark web.… More >

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