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Author: Alex A. Freitas
Publisher: Springer Science & Business Media
ISBN: 1461555213
Category : Computers
Languages : en
Pages : 211
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Book Description
Mining Very Large Databases with Parallel Processing addresses the problem of large-scale data mining. It is an interdisciplinary text, describing advances in the integration of three computer science areas, namely `intelligent' (machine learning-based) data mining techniques, relational databases and parallel processing. The basic idea is to use concepts and techniques of the latter two areas - particularly parallel processing - to speed up and scale up data mining algorithms. The book is divided into three parts. The first part presents a comprehensive review of intelligent data mining techniques such as rule induction, instance-based learning, neural networks and genetic algorithms. Likewise, the second part presents a comprehensive review of parallel processing and parallel databases. Each of these parts includes an overview of commercially-available, state-of-the-art tools. The third part deals with the application of parallel processing to data mining. The emphasis is on finding generic, cost-effective solutions for realistic data volumes. Two parallel computational environments are discussed, the first excluding the use of commercial-strength DBMS, and the second using parallel DBMS servers. It is assumed that the reader has a knowledge roughly equivalent to a first degree (BSc) in accurate sciences, so that (s)he is reasonably familiar with basic concepts of statistics and computer science. The primary audience for Mining Very Large Databases with Parallel Processing is industry data miners and practitioners in general, who would like to apply intelligent data mining techniques to large amounts of data. The book will also be of interest to academic researchers and postgraduate students, particularly database researchers, interested in advanced, intelligent database applications, and artificial intelligence researchers interested in industrial, real-world applications of machine learning.
Author: Alex A. Freitas
Publisher: Springer Science & Business Media
ISBN: 1461555213
Category : Computers
Languages : en
Pages : 211
Get Book Here
Book Description
Mining Very Large Databases with Parallel Processing addresses the problem of large-scale data mining. It is an interdisciplinary text, describing advances in the integration of three computer science areas, namely `intelligent' (machine learning-based) data mining techniques, relational databases and parallel processing. The basic idea is to use concepts and techniques of the latter two areas - particularly parallel processing - to speed up and scale up data mining algorithms. The book is divided into three parts. The first part presents a comprehensive review of intelligent data mining techniques such as rule induction, instance-based learning, neural networks and genetic algorithms. Likewise, the second part presents a comprehensive review of parallel processing and parallel databases. Each of these parts includes an overview of commercially-available, state-of-the-art tools. The third part deals with the application of parallel processing to data mining. The emphasis is on finding generic, cost-effective solutions for realistic data volumes. Two parallel computational environments are discussed, the first excluding the use of commercial-strength DBMS, and the second using parallel DBMS servers. It is assumed that the reader has a knowledge roughly equivalent to a first degree (BSc) in accurate sciences, so that (s)he is reasonably familiar with basic concepts of statistics and computer science. The primary audience for Mining Very Large Databases with Parallel Processing is industry data miners and practitioners in general, who would like to apply intelligent data mining techniques to large amounts of data. The book will also be of interest to academic researchers and postgraduate students, particularly database researchers, interested in advanced, intelligent database applications, and artificial intelligence researchers interested in industrial, real-world applications of machine learning.
Author: Jure Leskovec
Publisher: Cambridge University Press
ISBN: 1107077230
Category : Computers
Languages : en
Pages : 480
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Book Description
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Author: Jyotsna Kumar Mandal
Publisher: Springer
ISBN: 9811020353
Category : Technology & Engineering
Languages : en
Pages : 686
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Book Description
The book covers a wide range of topics in Computer Science and Information Technology including swarm intelligence, artificial intelligence, evolutionary algorithms, and bio-inspired algorithms. It is a collection of papers presented at the First International Conference on Intelligent Computing and Communication (ICIC2) 2016. The prime areas of the conference are Intelligent Computing, Intelligent Communication, Bio-informatics, Geo-informatics, Algorithm, Graphics and Image Processing, Graph Labeling, Web Security, Privacy and e-Commerce, Computational Geometry, Service Orient Architecture, and Data Engineering.
Author: Alex A. Freitas
Publisher: Springer Science & Business Media
ISBN: 3662049236
Category : Computers
Languages : en
Pages : 272
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Book Description
This book integrates two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increasingly popular in the last few years, and their integration is currently an active research area. In general, data mining consists of extracting knowledge from data. The motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions. This book emphasizes the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making. The text explains both basic concepts and advanced topics
Author: Burkhard Monien
Publisher: Springer
ISBN: 3540457062
Category : Computers
Languages : en
Pages : 1017
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Book Description
Euro-Par – the European Conference on Parallel Computing – is an international conference series dedicated to the promotion and advancement of all aspects of parallel computing. The major themes can be divided into the broad categories of hardware, software, algorithms, and applications for parallel computing. The objective of Euro-Par is to provide a forum within which to promote the dev- opment of parallel computing both as an industrial technique and an academic discipline, extending the frontiers of both the state of the art and the state of the practice. This is particularlyimportant at a time when parallel computing is undergoing strong and sustained development and experiencing real industrial take-up. The main audience for and participants in Euro-Par are researchers in academic departments, government laboratories, and industrial organizations. Euro-Par aims to become the primarychoice of such professionals for the p- sentation of new results in their speci?c areas. Euro-Par is also interested in applications that demonstrate the e?ectiveness of the main Euro-Par themes. Euro-Par has its own Internet domain with a permanent website where the historyof the conference series is described: http://www. euro-par. org. The Euro-Par conference series is sponsored bythe Association of Computer - chineryand the International Federation of Information Processing. Euro-Par 2002 at Paderborn, Germany Euro-Par 2002 was organized bythe Paderborn Center for Parallel Comput- 2 2 ing (PC ) and was held at the Heinz Nixdorf MuseumsForum (HNF).
Author: Jose Rolim
Publisher: Springer
ISBN: 3540455914
Category : Computers
Languages : en
Pages : 667
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Book Description
This volume contains the proceedings from the workshops held in conjunction with the IEEE International Parallel and Distributed Processing Symposium, IPDPS 2000, on 1-5 May 2000 in Cancun, Mexico. The workshopsprovidea forum for bringing together researchers,practiti- ers, and designers from various backgrounds to discuss the state of the art in parallelism.Theyfocusondi erentaspectsofparallelism,fromruntimesystems to formal methods, from optics to irregular problems, from biology to networks of personal computers, from embedded systems to programming environments; the following workshops are represented in this volume: { Workshop on Personal Computer Based Networks of Workstations { Workshop on Advances in Parallel and Distributed Computational Models { Workshop on Par. and Dist. Comp. in Image, Video, and Multimedia { Workshop on High-Level Parallel Prog. Models and Supportive Env. { Workshop on High Performance Data Mining { Workshop on Solving Irregularly Structured Problems in Parallel { Workshop on Java for Parallel and Distributed Computing { WorkshoponBiologicallyInspiredSolutionsto ParallelProcessingProblems { Workshop on Parallel and Distributed Real-Time Systems { Workshop on Embedded HPC Systems and Applications { Recon gurable Architectures Workshop { Workshop on Formal Methods for Parallel Programming { Workshop on Optics and Computer Science { Workshop on Run-Time Systems for Parallel Programming { Workshop on Fault-Tolerant Parallel and Distributed Systems All papers published in the workshops proceedings were selected by the p- gram committee on the basis of referee reports. Each paper was reviewed by independent referees who judged the papers for originality, quality, and cons- tency with the themes of the workshops.
Author: Management Association, Information Resources
Publisher: IGI Global
ISBN: 1522551921
Category : Computers
Languages : en
Pages : 2373
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Book Description
With the increased use of technology in modern society, high volumes of multimedia information exists. It is important for businesses, organizations, and individuals to understand how to optimize this data and new methods are emerging for more efficient information management and retrieval. Information Retrieval and Management: Concepts, Methodologies, Tools, and Applications is an innovative reference source for the latest academic material in the field of information and communication technologies and explores how complex information systems interact with and affect one another. Highlighting a range of topics such as knowledge discovery, semantic web, and information resources management, this multi-volume book is ideally designed for researchers, developers, managers, strategic planners, and advanced-level students.
Author: M. Emre Celebi
Publisher: Springer
ISBN: 3319092596
Category : Technology & Engineering
Languages : en
Pages : 420
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Book Description
This book focuses on partitional clustering algorithms, which are commonly used in engineering and computer scientific applications. The goal of this volume is to summarize the state-of-the-art in partitional clustering. The book includes such topics as center-based clustering, competitive learning clustering and density-based clustering. Each chapter is contributed by a leading expert in the field.
Author: Craig A. Lee
Publisher: Springer Science & Business Media
ISBN: 3540429492
Category : Computers
Languages : en
Pages : 197
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Book Description
This book constitutes the refereed proceedings of the Second International Workshop on Grid Computing, GRID 2001, held in Denver, CO, USA, in November 2001. The 16 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on object middleware, resource discovery and management, scheduling, grid architecture and policies, and performance and practice.
Author: Juha Fagerholm
Publisher: Springer
ISBN: 354048051X
Category : Computers
Languages : en
Pages : 597
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Book Description
This book constitutes the refereed proceedings of the 6th International Conference on Applied Parallel Computing, PARA 2002, held in Espoo, Finland, in June 2002. The 50 revised full papers presented together with nine keynote lectures were carefully reviewed and selected for inclusion in the proceedings. The papers are organized in topical sections on data mining and knowledge discovery, parallel program development, practical experience in parallel computing, computer science, numerical algorithms with hierarchical memory optimization, numerical methods and algorithms, cluster computing, grid and network technologies, and physics and applications.
