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Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Neha Sharma,Amlan Chakrabarti,Jan Martinovic Conference proceedings 2021 Sp

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书目名称Data Management, Analytics and Innovation
副标题Proceedings of ICDMA
编辑Neha Sharma,Amlan Chakrabarti,Jan Martinovic
视频video
概述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 resear
丛书名称Advances in Intelligent Systems and Computing
图书封面Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Neha Sharma,Amlan Chakrabarti,Jan Martinovic Conference proceedings 2021 Sp
描述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 Featuring original, unpublished contributions by respected experts from around the globe, the book is mainly intended for a professional audience of researchers and practitioners in academia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. 
出版日期Conference proceedings 2021
关键词Data Exchange; Data Management; Agricultural Informatics; Computational Economics; Information Ecology; I
版次1
doihttps://doi.org/10.1007/978-981-15-5619-7
isbn_softcover978-981-15-5618-0
isbn_ebook978-981-15-5619-7Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer Nature Singapore Pte Ltd. 2021
The information of publication is updating

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Quantum Machine Learning: A Review and Current Statusum machine learning investigates how results from the quantum world can be used to solve problems from machine learning. The amount of data needed to reliably train a classical computation model is evergrowing and reaching the limits which normal computing devices can handle. In such a scenario, qua
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An Efficient Algorithm for Complete Linkage Clustering with a Merging Thresholdp at a high speed. Apart from collecting this avalanche of data, another major problem is extracting useful information from it. Clustering is a highly powerful data mining tool capable of finding hidden information from a totally unlabelled dataset. Complete Linkage Clustering is a distance-based H
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