Data Mining Techniques In Grid Computing Environments
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Data Mining Techniques in Grid Computing Environments by Werner Dubitzky Pdf
Based around eleven international real life case studies and including contributions from leading experts in the field this groundbreaking book explores the need for the grid-enabling of data mining applications and provides a comprehensive study of the technology, techniques and management skills necessary to create them. This book provides a simultaneous design blueprint, user guide, and research agenda for current and future developments and will appeal to a broad audience; from developers and users of data mining and grid technology, to advanced undergraduate and postgraduate students interested in this field.
Techniques and Environments for Big Data Analysis by B. S.P. Mishra,Satchidananda Dehuri,Euiwhan Kim,Gi-Name Wang Pdf
This volume is aiming at a wide range of readers and researchers in the area of Big Data by presenting the recent advances in the fields of Big Data Analysis, as well as the techniques and tools used to analyze it. The book includes 10 distinct chapters providing a concise introduction to Big Data Analysis and recent Techniques and Environments for Big Data Analysis. It gives insight into how the expensive fitness evaluation of evolutionary learning can play a vital role in big data analysis by adopting Parallel, Grid, and Cloud computing environments.
Grid and Cloud Computing: Concepts, Methodologies, Tools and Applications by Management Association, Information Resources Pdf
"This reference presents a vital compendium of research detailing the latest case studies, architectures, frameworks, methodologies, and research on Grid and Cloud Computing"--
Model and Data Engineering by Ladjel Bellatreche,Filipe Mota Pinto Pdf
This book constitutes the refereed proceedings of the First International Conference on Model and Data Engineering, MEDI 2011, held in Óbidos, Portugal, in September 2011. The 18 revised full papers presented together with 8 short papers and three keynotes were carefully reviewed and selected from 67 submissions. The papers are organized in topical sections on ontology engineering; Web services and security; advanced systems; knowledge management; model specification and verification; and models engineering.
Pocket Data Mining by Mohamed Medhat Gaber,Frederic Stahl,João Bártolo Gomes Pdf
Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.
Service-Oriented Distributed Knowledge Discovery by Domenico Talia,Paolo Trunfio Pdf
A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today’s often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniques, algorithms, and systems based on the service-oriented paradigm. Through detailed descriptions of real software systems, it shows how the techniques, models, and architectures can be implemented. The book covers key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and service-oriented data mining. The authors illustrate how to design services for data analytics, describe real systems for implementing distributed knowledge discovery applications, and explore mobile data mining models. They also discuss the future role of service-oriented knowledge discovery in ubiquitous discovery processes and large-scale data analytics. Highlighting the latest achievements in the field, the book gives many examples of the state of the art in service-oriented knowledge discovery. Both novices and more seasoned researchers will learn useful concepts related to distributed data mining and service-oriented data analysis. Developers will also gain insight on how to successfully use service-oriented knowledge discovery in databases (KDD) frameworks.
Web Usage Mining Techniques and Applications Across Industries by Kumar, A.V. Senthil Pdf
Web usage mining is defined as the application of data mining technologies to online usage patterns as a way to better understand and serve the needs of web-based applications. Because the internet has become a central component in information sharing and commerce, having the ability to analyze user behavior on the web has become a critical component to a variety of industries. Web Usage Mining Techniques and Applications Across Industries addresses the systems and methodologies that enable organizations to predict web user behavior as a way to support website design and personalization of web-based services and commerce. Featuring perspectives from a variety of sectors, this publication is designed for use by IT specialists, business professionals, researchers, and graduate-level students interested in learning more about the latest concepts related to web-based information retrieval and mining.
Grid and Cloud Database Management by Sandro Fiore,Giovanni Aloisio Pdf
Since the 1990s Grid Computing has emerged as a paradigm for accessing and managing distributed, heterogeneous and geographically spread resources, promising that we will be able to access computer power as easily as we can access the electric power grid. Later on, Cloud Computing brought the promise of providing easy and inexpensive access to remote hardware and storage resources. Exploiting pay-per-use models and virtualization for resource provisioning, cloud computing has been rapidly accepted and used by researchers, scientists and industries. In this volume, contributions from internationally recognized experts describe the latest findings on challenging topics related to grid and cloud database management. By exploring current and future developments, they provide a thorough understanding of the principles and techniques involved in these fields. The presented topics are well balanced and complementary, and they range from well-known research projects and real case studies to standards and specifications, and non-functional aspects such as security, performance and scalability. Following an initial introduction by the editors, the contributions are organized into four sections: Open Standards and Specifications, Research Efforts in Grid Database Management, Cloud Data Management, and Scientific Case Studies. With this presentation, the book serves mostly researchers and graduate students, both as an introduction to and as a technical reference for grid and cloud database management. The detailed descriptions of research prototypes dealing with spatiotemporal or genomic data will also be useful for application engineers in these fields.
Advanced Data Mining and Applications by Ronghuai Huang,Qiang Yang,Jian Pei,João Gama,Xiaofeng Meng,Xue Li Pdf
This book constitutes the refereed proceedings of the 5th International Conference on Advanced Data Mining and Applications, ADMA 2009, held in Beijing, China, in August 2009. The 34 revised full papers and 47 revised short papers presented together with the abstract of 4 keynote lectures were carefully reviewed and selected from 322 submissions from 27 countries. The papers focus on advancements in data mining and peculiarities and challenges of real world applications using data mining and feature original research results in data mining, spanning applications, algorithms, software and systems, and different applied disciplines with potential in data mining.
This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in analysis of large data sets, through the explanation of basic concepts, models and methodologies developed in recent decades. If you are an instructor or professor and would like to obtain instructor’s materials, please visit http://booksupport.wiley.com If you are an instructor or professor and would like to obtain a solutions manual, please send an email to: [email protected]
Marian Bubak,Geert Dick van Albada,Jack Dongarra,Peter M.A. Sloot
Author : Marian Bubak,Geert Dick van Albada,Jack Dongarra,Peter M.A. Sloot Publisher : Springer Science & Business Media Page : 769 pages File Size : 40,6 Mb Release : 2008-06-11 Category : Computers ISBN : 9783540693888
Computational Science – ICCS 2008 by Marian Bubak,Geert Dick van Albada,Jack Dongarra,Peter M.A. Sloot Pdf
The three-volume set LNCS 5101-5103 constitutes the refereed proceedings of the 8th International Conference on Computational Science, ICCS 2008, held in Krakow, Poland in June 2008. The 167 revised papers of the main conference track presented together with the abstracts of 7 keynote talks and the 100 revised papers from 14 workshops were carefully reviewed and selected for inclusion in the three volumes. The main conference track was divided into approximately 20 parallel sessions addressing topics such as e-science applications and systems, scheduling and load balancing, software services and tools, new hardware and its applications, computer networks, simulation of complex systems, image processing and visualization, optimization techniques, numerical linear algebra, and numerical algorithms. The second volume contains workshop papers related to various computational research areas, e.g.: computer graphics and geometric modeling, simulation of multiphysics multiscale systems, computational chemistry and its applications, computational finance and business intelligence, physical, biological and social networks, geocomputation, and teaching computational science. The third volume is mostly related to computer science topics such as bioinformatics' challenges to computer science, tools for program development and analysis in computational science, software engineering for large-scale computing, collaborative and cooperative environments, applications of workflows in computational science, as well as intelligent agents and evolvable systems.
Distributed Data Management for Grid Computing by Michael Di Stefano Pdf
Discover grid computing-how to successfully build, implement, and manage widely distributed computing architecture With technology budgets under increasing scrutiny and system architecture becoming more and more complex, many organizations are rethinking how they manage and use technology. Keeping a strong business focus, this publication clearly demonstrates that the current ways of tying applications to dedicated hardware are no longer viable in today's competitive, bottom line-oriented environment. This evolution in distributed computing is leading a paradigm shift in leveraging widely distributed architectures to get the most processing power per IT dollar. Presenting a solid foundation of data management issues and techniques, this practical book delves into grid architecture, services, practices, and much more, including: * Why businesses should adopt grid computing * How to master the fundamental concepts and programming techniques and apply them successfully to reach objectives * How to maximize the value of existing IT investments The author has tailored this publication for two distinct audiences. Business professionals will gain a better understanding of how grid computing improves productivity and performance, what impact it can have on their organization's bottom line, and the technical foundations necessary to discuss grid computing with their IT colleagues. Following the author's expert guidance and practical examples, IT professionals, architects, and developers will be equipped to initiate and carry out successful grid computing projects within their own organizations.
Service-Oriented Distributed Knowledge Discovery by Domenico Talia,Paolo Trunfio Pdf
A new approach to distributed large-scale data mining, service-oriented knowledge discovery extracts useful knowledge from today’s often unmanageable volumes of data by exploiting data mining and machine learning distributed models and techniques in service-oriented infrastructures. Service-Oriented Distributed Knowledge Discovery presents techniques, algorithms, and systems based on the service-oriented paradigm. Through detailed descriptions of real software systems, it shows how the techniques, models, and architectures can be implemented. The book covers key areas in data mining and service-oriented computing. It presents the concepts and principles of distributed knowledge discovery and service-oriented data mining. The authors illustrate how to design services for data analytics, describe real systems for implementing distributed knowledge discovery applications, and explore mobile data mining models. They also discuss the future role of service-oriented knowledge discovery in ubiquitous discovery processes and large-scale data analytics. Highlighting the latest achievements in the field, the book gives many examples of the state of the art in service-oriented knowledge discovery. Both novices and more seasoned researchers will learn useful concepts related to distributed data mining and service-oriented data analysis. Developers will also gain insight on how to successfully use service-oriented knowledge discovery in databases (KDD) frameworks.
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.
Grid Computing: Software Environments and Tools by Omer F. Rana,Jose Cardoso Cunha Pdf
Grid Computing requires the use of software that can divide and farm out pieces of a program to as many as several thousand computers. This book explores processes and techniques needed to create a successful Grid infrastructure. Leading researchers in Europe and the US look at the development of specialist tools and environments which will encourage the convergence of the parallel programming, distributed computing and data management communities. Specific topics covered include: An overview of structural and behavioural properties of Computer Grid applications Discussion of alternative programming techniques Case studies displaying the potential of Computer Grids in solving real problems This book is unique in its outline of the needs of Computational Grids both in integration of high-end resources using OGSA/Globus, and the loose integration of Peer-2-Peer/Entropia/United Devices. Readers will gain an insight on the limitations of existing approaches as well as the standardisation activities currently taking place.