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Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Valentina Emilia Balas,Neha Sharma,Amlan Chakrabar Conference proceedings 2

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書(shū)目名稱Data Management, Analytics and Innovation
副標(biāo)題Proceedings of ICDMA
編輯Valentina Emilia Balas,Neha Sharma,Amlan Chakrabar
視頻videohttp://file.papertrans.cn/263/262882/262882.mp4
概述Presents the latest research findings in the areas of data management and data analytics.Discusses state-of-the-art topics as well as the challenges and solutions for future development.Serves as a re
叢書(shū)名稱Advances in Intelligent Systems and Computing
圖書(shū)封面Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Valentina Emilia Balas,Neha Sharma,Amlan Chakrabar Conference proceedings 2
描述.The book presents the latest, high-quality, technical contributions and research findings in the areas of data management and smart computing, big data management, artificial intelligence and data analytics, along with advances in network technologies. It discusses state-of-the-art topics as well as the challenges and solutions for future development. It includes original and previously unpublished international research work highlighting research domains from different perspectives. This book is mainly intended for researchers and practitioners in academia and industry..
出版日期Conference proceedings 2019
關(guān)鍵詞Data Exchange; Data Management; ICDMAI Proceedings; DMAI 2018; Agricultural Informatics; Community Inform
版次1
doihttps://doi.org/10.1007/978-981-13-1402-5
isbn_softcover978-981-13-1401-8
isbn_ebook978-981-13-1402-5Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer Nature Singapore Pte Ltd. 2019
The information of publication is updating

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https://doi.org/10.1007/978-1-4684-4250-2 truck of that area that the bin in his vicinity needs to be emptied. A shortest path to empty all the filled bins or the bins with the threshold level is also displayed on the mobile application that saves fuel and time and more work can be done. When the bin is filled or senses hazardous gas using
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Building Aspectual Interpretations Online performance of the algorithm on the traffic network data from the city of Bratislava, Slovakia to prove that the inclusion of the modification does not hinder the original algorithm much. We also provide a visualization of the traffic network of the city of Ostrava, the Czech Republic to show the e
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https://doi.org/10.1007/978-1-4612-5519-2to provide adequate support to the decision making process. BI represents a family of products that includes Data mining Algorithms, Data mining products for creating reports. Improving efficiency in this process is discussed in this work. The M-Clustering algorithm which is conceived in this work p
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Architecture and Representationscation problem. The data that is available in the form of tweets on twitter can easily frame the insight of the public attitude towards the particular tweet. The proposed work is well planned to design as well as implement the best hybrid method that includes Hybrid Kmeans/Modified Kmeans (MKmeans)
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David Philipona,J. Kevin O’Reganfurther classified as top-down and bottom-up algorithms depending on strategy applied to identify subspaces. Initial clustering in case of top-down algorithms is based on full set of dimensions and it then iterates to identify subset of dimensions which can better represent the subspaces by removing
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Smart Waste Management for Segregating Different Types of Wastes truck of that area that the bin in his vicinity needs to be emptied. A shortest path to empty all the filled bins or the bins with the threshold level is also displayed on the mobile application that saves fuel and time and more work can be done. When the bin is filled or senses hazardous gas using
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