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Author: Wookey Lee Publisher: Springer ISBN: 9811065209 Category : Technology & Engineering Languages : en Pages : 349
Book Description
This proceedings volume presents selected papers from the 7th International Conference on Emerging Databases: Technologies, Applications, and Theory (EDB 2017), which was held in Busan, Korea from 7 to 9 August, 2017. This conference series was launched by the Korean Institute of Information Scientists and Engineers (KIISE) Database Society of Korea as an annual forum for exploring novel technologies, applications, and research advances in the field of emerging databases. This forum has evolved into the premier international venue for researchers and practitioners to discuss current research issues, challenges, new technologies, and solutions.
Author: Wookey Lee Publisher: Springer ISBN: 9811065209 Category : Technology & Engineering Languages : en Pages : 349
Book Description
This proceedings volume presents selected papers from the 7th International Conference on Emerging Databases: Technologies, Applications, and Theory (EDB 2017), which was held in Busan, Korea from 7 to 9 August, 2017. This conference series was launched by the Korean Institute of Information Scientists and Engineers (KIISE) Database Society of Korea as an annual forum for exploring novel technologies, applications, and research advances in the field of emerging databases. This forum has evolved into the premier international venue for researchers and practitioners to discuss current research issues, challenges, new technologies, and solutions.
Author: Sven Hartmann Publisher: Springer ISBN: 3319988093 Category : Computers Languages : en Pages : 495
Book Description
This two volume set of LNCS 11029 and LNCS 11030 constitutes the refereed proceedings of the 29th International Conference on Database and Expert Systems Applications, DEXA 2018, held in Regensburg, Germany, in September 2018. The 35 revised full papers presented together with 40 short papers were carefully reviewed and selected from 160 submissions. The papers of the first volume discuss a range of topics including: Big data analytics; data integrity and privacy; decision support systems; data semantics; cloud data processing; time series data; social networks; temporal and spatial databases; and graph data and road networks. The papers of the second volume discuss a range of the following topics: Information retrieval; uncertain information; data warehouses and recommender systems; data streams; information networks and algorithms; database system architecture and performance; novel database solutions; graph querying and databases; learning; emerging applications; data mining; privacy; and text processing.
Author: Wookey Lee Publisher: Springer Nature ISBN: 9811587310 Category : Technology & Engineering Languages : en Pages : 127
Book Description
This book covers topics like big data analyses, services, and smart data. It contains (i) invited papers, (ii) selected papers from the Sixth International Conference on Big Data Applications and Services (BigDAS 2018), as well as (iii) extended papers from the Sixth IEEE International Conference on Big Data and Smart Computing (IEEE BigComp 2019). The aim of BigDAS is to present innovative results, encourage academic and industrial interaction, and promote collaborative research in the field of big data worldwide. BigDAS 2018 was held in Zhengzhou, China, on August 19–22, 2018, and organized by the Korea Big Data Service Society and TusStar. The goal of IEEE BigComp, initiated by Korean Institute of Information Scientists and Engineers (KIISE), is to provide an international forum for exchanging ideas and information on current studies, challenges, research results, system developments, and practical experiences in the emerging fields of big data and smart computing. IEEE BigComp 2019 was held in Kyoto, Japan, on February 27–March 02, 2019, and co-sponsored by IEEE and KIISE.
Author: L. Ashok Kumar Publisher: Springer Nature ISBN: 3030240517 Category : Technology & Engineering Languages : en Pages : 943
Book Description
Due to the complexity, and heterogeneity of the smart grid and the high volume of information to be processed, artificial intelligence techniques and computational intelligence appear to be some of the enabling technologies for its future development and success. The theme of the book is “Making pathway for the grid of future” with the emphasis on trends in Smart Grid, renewable interconnection issues, planning-operation-control and reliability of grid, real time monitoring and protection, market, distributed generation and power distribution issues, power electronics applications, computer-IT and signal processing applications, power apparatus, power engineering education and industry-institute collaboration. The primary objective of the book is to review the current state of the art of the most relevant artificial intelligence techniques applied to the different issues that arise in the smart grid development.
Author: Publisher: Elsevier ISBN: 0323898114 Category : Computers Languages : en Pages : 460
Book Description
Principles of Big Graph: In-depth Insight, Volume 128 in the Advances in Computer series, highlights new advances in the field with this new volume presenting interesting chapters on a variety of topics, including CESDAM: Centered subgraph data matrix for large graph representation, Bivariate, cluster and suitability analysis of NoSQL Solutions for big graph applications, An empirical investigation on Big Graph using deep learning, Analyzing correlation between quality and accuracy of graph clustering, geneBF: Filtering protein-coded gene graph data using bloom filter, Processing large graphs with an alternative representation, MapReduce based convolutional graph neural networks: A comprehensive review. Fast exact triangle counting in large graphs using SIMD acceleration, A comprehensive investigation on attack graphs, Qubit representation of a binary tree and its operations in quantum computation, Modified ML-KNN: Role of similarity measures and nearest neighbor configuration in multi label text classification on big social network graph data, Big graph based online learning through social networks, Community detection in large-scale real-world networks, Power rank: An interactive web page ranking algorithm, GA based energy efficient modelling of a wireless sensor network, The major challenges of big graph and their solutions: A review, and An investigation on socio-cyber crime graph. Provides an update on the issues and challenges faced by current researchers Updates on future research agendas Includes advanced topics for intensive research for researchers
Author: James Lee Publisher: Packt Publishing Ltd ISBN: 1788626087 Category : Computers Languages : en Pages : 293
Book Description
Solve all big data problems by learning how to create efficient data models Key FeaturesCreate effective models that get the most out of big dataApply your knowledge to datasets from Twitter and weather data to learn big dataTackle different data modeling challenges with expert techniques presented in this bookBook Description Modeling and managing data is a central focus of all big data projects. In fact, a database is considered to be effective only if you have a logical and sophisticated data model. This book will help you develop practical skills in modeling your own big data projects and improve the performance of analytical queries for your specific business requirements. To start with, you’ll get a quick introduction to big data and understand the different data modeling and data management platforms for big data. Then you’ll work with structured and semi-structured data with the help of real-life examples. Once you’ve got to grips with the basics, you’ll use the SQL Developer Data Modeler to create your own data models containing different file types such as CSV, XML, and JSON. You’ll also learn to create graph data models and explore data modeling with streaming data using real-world datasets. By the end of this book, you’ll be able to design and develop efficient data models for varying data sizes easily and efficiently. What you will learnGet insights into big data and discover various data modelsExplore conceptual, logical, and big data modelsUnderstand how to model data containing different file typesRun through data modeling with examples of Twitter, Bitcoin, IMDB and weather data modelingCreate data models such as Graph Data and Vector SpaceModel structured and unstructured data using Python and RWho this book is for This book is great for programmers, geologists, biologists, and every professional who deals with spatial data. If you want to learn how to handle GIS, GPS, and remote sensing data, then this book is for you. Basic knowledge of R and QGIS would be helpful.
Author: Abdelkader Hameurlain Publisher: Springer ISBN: 3662478048 Category : Computers Languages : en Pages : 198
Book Description
The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This volume, the 21st issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, focuses on Data Warehousing and Knowledge Discovery from Big Data, and contains extended and revised versions of eight papers selected as the best papers from the 14th International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2012), held in Vienna, Austria, during September 3-6, 2012. These papers cover several advanced Big Data topics, ranging from data cube computation using MapReduce to multiple aggregations over multidimensional databases, from data warehousing systems over complex energy data to OLAP-based prediction models, from extended query engines for continuous stream analytics to popular pattern mining, and from rare pattern mining to enhanced knowledge discovery from large cross-document corpora.
Author: Wookey Lee
Author: Wookey Lee
Author: Murat Altug Erberik
Author: Ma, Zongmin
Author: Sven Hartmann
Author: Wookey Lee
Author: L. Ashok Kumar
Author: 
Author: James Lee
Author: Victor Pankratius
Author: Abdelkader Hameurlain