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Big Data Computing for Geospatial Applications

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Big Data

Big data has always been a major challenge in geoinformatics as geospatial data come in various types and formats, new geospatial data are;

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Big Data

Big data has always been a major challenge in geoinformatics as geospatial data come in various types and formats, new geospatial data are;

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Handbook of Big Geospatial Data

reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as;

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Geospacial Computing In Mobile Devices

aspects related to positioning methods, as well as solutions for geospatial data acquisition, processing, and visualization. This resource also;

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Geospatial Data Science Techniques and Applications

Data science has recently gained much attention for a number of reasons, and among them is Big Data. Scientists (from almost all;

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Spatial Data Handling in Big Data Era

This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial;

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Smart Data

, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art;

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Spatial Data Handling in Big Data Era

This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial;

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Security and Privacy for Big Data, Cloud Computing and Applications

As big data becomes increasingly pervasive and cloud computing utilization becomes the norm, the security and privacy of our systems and;

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Smart Data

, Big Data capture and representation, AI for Big Data applications, and more. Features Presents state-of-the-art research;

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Big Data Computing

to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data;

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Machine Learning Approaches for Urban Computing

details multiple types of data generating from urban activities and suitability of various machine learning algorithms for handling urban data;

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Internet Computing and Big Data

Internet Computing and Big Data is a compendium of articles and papers that were presented at ICOMP '13, an international conference that;

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Big Data Analytics for Sustainable Computing

Big data consists of data sets that are too large and complex for traditional data processing and data management applications. Therefore;

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Big Data Technologies and Applications

fraud, Ebola spread modeling using big data analytics, unsupervised learning, and image classification. The book is intended for a wide variety;

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Big Data Management and Processing

, as well as legal compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co;

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Big Data Management and Processing

compliance and quality management for Big Data. It covers In-Memory computing and In-Memory data grids, as well as co-scheduling for high performance;

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High Performance Computing for Big Data

High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive;

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High Performance Computing for Big Data

High-Performance Computing for Big Data: Methodologies and Applications explores emerging high-performance architectures for data-intensive;

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Systems Simulation and Modeling for Cloud Computing and Big Data Applications

Systems Simulation and Modelling for Cloud Computing and Big Data Applications provides readers with the most current approaches to;

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Python Geospatial Development - Third Edition

applications based around maps and geospatial data using Python 3.x * Install and use various toolkits and obtain geospatial data for use in your;

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Practical Concurrent Haskell

processing on big data using Haskell Use MapReduce and work with Haskell on large clusters Who This Book Is For Those with at least some;

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High Performance Big Data Computing

and benchmarking, and system deployment and management; and surveys benchmarks and workloads for evaluating big data middleware systems. It;

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GIS and the 2020 Census

technologies for field data collection and operations management. After planning and collecting data, apply innovative solutions for performing;

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Big-Data Analytics for Cloud, IoT and Cognitive Computing

analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data;

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Advances on Smart and Soft Computing

, big data analytics, smart computing, smart cities, Internet of things (IoT), data communication, cloud computing, machine learning algorithms;

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