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Data Intensive Distributed Computing

Data Intensive Distributed Computing: Challenges and Solutions for Large-scale Information Management focuses on the challenges;

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Identification and Management of Distributed Data

software technologies for identifying, addressing, and managing distributed data. Focusing on this convergence, Identification and Management;

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Identification and Management of Distributed Data

software technologies for identifying, addressing, and managing distributed data. Focusing on this convergence, Identification and Management;

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Distributed Database Architecture

In distributed systems, clients access data that is stored in multiple server locations. The computers in a distributed system are called;

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Bsns Dt Comm Mv

'Business Data Communications' covers the fundamentals of data communications, networking, distributed applications, and network management;

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SQL Server 2000

This volume covers basic to advanced topics, including the management and access of distributed data, as well as the creation and;

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Transactions on Large-Scale Data- and Knowledge-Centered Systems XLIV

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and;

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Cloud Computing in Remote Sensing

a series of remote sensing data management and processing standards. Features: Covers remote sensing cloud computing Covers;

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Big Data and Computational Intelligence in Networking

comprehensive understanding of network big data, efficient collection and management of network big data, distributed and scalable online analytics for;

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Transactions on Large-Scale Data- and Knowledge-Centered Systems XLVIII

include distributed database systems, NewSQL, scalable transaction management, strong consistency, caches, data warehouse, ETL, reinforcement;

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Distributed Data Fusion for Network-Centric Operations

, distributed fusion is taking on a larger role in a variety of applications-from environmental monitoring and crisis management to intelligent;

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Distributed Machine Learning and Gradient Optimization

in the field of machine learning, artificial intelligence, big data and database management.;

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Knowledge and Data Management in GRIDs

research results in key areas such as distributed storage management, Grid databases, Semantic Grid and Grid-aware data mining. Written for a;

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Data Analytics and Management in Data Intensive Domains

This book constitutes the post-conference proceedings of the 21st International Conference on Data Analytics and Management in Data;

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Web-Age Information Management

temporal databases, recommender systems, graph data management, information retrieval, privacy and trust, query processing and optimization, social;

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Web-Age Information Management

temporal databases, recommender systems, graph data management, information retrieval, privacy and trust, query processing and optimization, social;

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Scientific and Statistical Database Management

, parallel and distributed data management, graph processing, mining multidimensional data, provenance and workflows, processing scientific queries;

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Cloud-Based RDF Data Management

the deployment of massively parallel data management tasks in a cloud environment. In this book, we study the state-of-the-art RDF data;

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Cloud-Based RDF Data Management

the deployment of massively parallel data management tasks in a cloud environment. In this book, we study the state-of-the-art RDF data;

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Cloud-Based RDF Data Management

the deployment of massively parallel data management tasks in a cloud environment. In this book, we study the state-of-the-art RDF data;

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Data Placement in Distributed Systems

requirements. Increasing data requirements and the distributed nature of the resources made I/O the major bottleneck for end-to-end application;

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Distributed Database Architecture

The book Distributed Database Architecture discusses various topics related to the database architecture. The technology of database;

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Knowledge Discovery from Sensor Data

presents innovative solutions in offline data mining and real-time analysis of sensor or geographically distributed data. It discusses the;

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Distributed Computing in Big Data Analytics

decision making. Principles of distributed computing are the keys to big data technologies and analytics. The mechanisms related to data storage;

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Distributed Data Mining and Mining Multi-Agent Data

The problem of distributed data mining is very important in networks. Ina distributed environment, one has distributed probes placed at;

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Distributed Database Management Systems

sampleframeworks implemented using J2SE with JMS, J2EE, andMicrosoft .Net that readers can use to learn how to implementa distributed database management;

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Concepts of Database Management

(including QBE and SQL), normalization and views, database administration and management. You also examine advanced topics such as distributed;

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