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Smart Data Intelligence : Proceedings of ICSMDI 2022 / edited by R. Asokan, Diego P. Ruiz, Zubair A. Baig, Selwyn Piramuthu

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Algorithms for Intelligent SystemsPublisher: Singapore : Springer Nature Singapore, 2022Publisher: Singapore : Imprint: Springer, 2022Edition: 1st ed. 2022Description: 1 Online-Ressource(XVI, 599 p. 287 illus., 222 illus. in color.)ISBN:
  • 9789811933110
Subject(s): Additional physical formats: 9789811933103 | 9789811933127 | 9789811933134 | Erscheint auch als: 9789811933103 Druck-Ausgabe | Erscheint auch als: 9789811933127 Druck-Ausgabe | Erscheint auch als: 9789811933134 Druck-AusgabeDOI: DOI: 10.1007/978-981-19-3311-0Online resources: Summary: Detection and Analysis of Sentiments on Twitter Using Machine Learning Algorithm -- Malware Attack Detection on IoT Devices Using Machine Learning -- BeSafe: IoT Based Safety Band -- Stock Market Analysis and forecasting with Statistical and Deep Learning Methods -- The paradigm shift in Higher Education from traditional learning to digitalisation -- Designing a socially intelligent system by cognitive modeling of human-environment interaction -- Web-Based recycle Waste Management for Ecommerce.Summary: This book presents high-quality research papers presented at 2nd International Conference on Smart Data Intelligence (ICSMDI 2022) organized by Kongunadu College of Engineering and Technology at Trichy, Tamil Nadu, India, during April 2022. This book brings out the new advances and research results in the fields of algorithmic design, data analysis, and implementation on various real-time applications. It discusses many emerging related fields like big data, data science, artificial intelligence, machine learning, and deep learning which have deployed a paradigm shift in various data-driven approaches that tends to evolve new data-driven research opportunities in various influential domains like social networks, healthcare, information, and communication applications.PPN: PPN: 1814988378Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-INR | ZDB-2-SXIT
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