Data Management, Analytics and Innovation, 1st ed. 2021 Proceedings of ICDMAI 2020, Volume 2 Advances in Intelligent Systems and Computing Series, Vol. 1175
Langue : Anglais
Coordonnateurs : Sharma Neha, Chakrabarti Amlan, Balas Valentina Emilia, Martinovic Jan
This book presents the latest findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. Gathering peer-reviewed research papers presented at the Fourth International Conference on Data Management, Analytics and Innovation (ICDMAI 2020), held on 17?19 January 2020 at the United Services Institute (USI), New Delhi, India, it addresses cutting-edge topics and discusses challenges and solutions for future development. Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia and industry.
Automatic Standardization of Data based on Machine Learning and Natural Language Processing.- Scoring Algorithm Identifying Anomalous Behavior in Enterprise Network.-APPLICATION OF BAYESIAN AUTOMATED HYPERPARAMETER TUNING ON CLASSIFIERS PREDICTING CUSTOMER RETENTION IN BANKING INDUSTRY.- Quantum Machine Learning: A Review and Current Status.- Survey of Transfer Learning and a Case Study of Emotion Recognition using Inductive Approach.- An Efficient Algorithm for Complete Linkage Clustering with a Merging Threshold.
Neha Sharma is working with Tata Consultancy Services and is a Founder Secretary, Society for Data Science, India. She has previously served as Director of ZIBACAR, Pune, India. Holding a Ph.D. from the prestigious Indian Institute of Technology, Dhanbad, she is a senior IEEE member and Executive Body member of the IEEE Pune Section. She has received a “Best PhD Thesis Award” and “Best Paper Presenter at International Conference Award” at the National Level from the Computer Society of India. Her research interests include data mining, database design, artificial intelligence, big data, cloud computing, blockchain and data science.
Amlan Chakrabarti is a Full Professor at the School of IT, University of Calcutta. He was a Postdoctoral Fellow at Princeton University, USA, from 2011 to 2012. With nearly 20 years of experience in Engineering Education and Research, he is a recipient of the prestigious DST BOYSCAST Fellowship Award in Engineering Science (2011), JSPS Invitation Research Award (2016), Erasmus Mundus Leaders Award from the EU (2017), and a Hamied Visiting Professorship from the University of Cambridge (2018). He is an Associate Editor of the Journal of Computers and Electrical Engineering, senior member of the IEEE and ACM, IEEE Computer Society Distinguished Visitor, Distinguished Speaker of the ACM, Secretary of the IEEE CEDA India Chapter and Vice President of the Data Science Society.
Prof. Valentina Emilia Balas is currently a Full Professor at the Department of Automatics and Applied Software, “Aurel Vlaicu” University of Arad, Romania. The author of more than 300 research papers, her research interests include intelligent systems, fuzzy control, soft computing, smart sensors, information fusion, modeling and simulation. She is the Editor-in-Chief of the Inderscience journals IJAIP and IJCSysE. She is the Director of the Department of International Relations and Hea
Presents cutting-edge research in the fields of data management, analytics, and innovation
Gathers the outcomes of ICDMAI 2020, held in New Delhi, India
Offers a valuable reference resource for researchers and practitioners in academia and industry
Date de parution : 09-2020
Ouvrage de 462 p.
15.5x23.5 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 158,24 €
Ajouter au panierThèmes de Data Management, Analytics and Innovation :
Mots-clés :
Data Exchange; Data Management; Agricultural Informatics; Computational Economics; Information Ecology; Irrigation Informatics; Neuroinformatics; Big Data; Big Data Analytics; Artificial Intelligence; Machine Learning; Evolutionary Computation Techniques; Mobile Robotics; Speech Recognition; Facial Detection; Heuristic and Genetic Algorithms; data structures
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