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  • Open Access

    ARTICLE

    Modeling and Predicting of News Popularity in Social Media Sources

    Kemal Akyol1,*, Baha Şen2

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 69-80, 2019, DOI:10.32604/cmc.2019.08143

    Abstract The popularity of news, which conveys newsworthy events which occur during day to people, is substantially important for the spectator or audience. People interact with news website and share news links or their opinions. This study uses supervised learning based machine learning techniques in order to predict news popularity in social media sources. These techniques consist of basically two phrases: a) the training data is sent as input to the classifier algorithm, b) the performance of pre-learned algorithm is tested on the testing data. And so, a knowledge discovery from the data is performed. In this context, firstly, twelve datasets… More >

  • Open Access

    ARTICLE

    Parkinson’s Disease Detection Using Biogeography-Based Optimization

    Somayeh Hessam1, Shaghayegh Vahdat1, Irvan Masoudi Asl2,*, Mahnaz Kazemipoor3, Atefeh Aghaei4, Shahaboddin Shamshirband,5,6,*, Timon Rabczuk7

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 11-26, 2019, DOI:10.32604/cmc.2019.06472

    Abstract In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0-disease status and 1- good control status. The performance of proposed methods compared with PSO, GA, ACO and ES method. The… More >

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