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  • Open Access


    SA-MSVM: Hybrid Heuristic Algorithm-based Feature Selection for Sentiment Analysis in Twitter

    C. P. Thamil Selvi1,*, R. PushpaLakshmi2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2439-2456, 2023, DOI:10.32604/csse.2023.029254

    Abstract One of the drastically growing and emerging research areas used in most information technology industries is Bigdata analytics. Bigdata is created from social websites like Facebook, WhatsApp, Twitter, etc. Opinions about products, persons, initiatives, political issues, research achievements, and entertainment are discussed on social websites. The unique data analytics method cannot be applied to various social websites since the data formats are different. Several approaches, techniques, and tools have been used for big data analytics, opinion mining, or sentiment analysis, but the accuracy is yet to be improved. The proposed work is motivated to do sentiment analysis on Twitter data… More >

  • Open Access


    Machine Learning Privacy Aware Anonymization Using MapReduce Based Neural Network

    U. Selvi*, S. Pushpa

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1185-1196, 2022, DOI:10.32604/iasc.2022.020164

    Abstract Due to the recent advancement in technologies, a huge amount of data is generated where individual private information needs to be preserved. A proper Anonymization algorithm with increased Data utility is required to protect individual privacy. However, preserving privacy of individuals whileprocessing huge amount of data is a challenging task, as the data contains certain sensitive information. Moreover, scalability issue in handling a large dataset is found in using existing framework. Many an Anonymization algorithm for Big Data have been developed and under research. We propose a method of applying Machine Learning techniques to protect and preserve the personal identities… More >

  • Open Access


    Preface of Special Issue on BigDataSE 2016

    Heng Qi1,2, Keqiu Li1

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 57-59, 2018, DOI:10.32604/csse.2018.33.057

    Abstract This article has no abstract. More >

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