Download or read book Large Scale Parallel Data Mining written by Mohammed J. Zaki and published by Springer. This book was released on 2003-07-31 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the unprecedented growth-rate at which data is being collected and stored electronically today in almost all fields of human endeavor, the efficient extraction of useful information from the data available is becoming an increasing scientific challenge and a massive economic need. This book presents thoroughly reviewed and revised full versions of papers presented at a workshop on the topic held during KDD'99 in San Diego, California, USA in August 1999 complemented by several invited chapters and a detailed introductory survey in order to provide complete coverage of the relevant issues. The contributions presented cover all major tasks in data mining including parallel and distributed mining frameworks, associations, sequences, clustering, and classification. All in all, the volume presents the state of the art in the young and dynamic field of parallel and distributed data mining methods. It will be a valuable source of reference for researchers and professionals.

Download or read book Large Scale Parallel Data Mining written by Mohammed J. Zaki and published by Springer. This book was released on 2000-02-23 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the unprecedented growth-rate at which data is being collected and stored electronically today in almost all fields of human endeavor, the efficient extraction of useful information from the data available is becoming an increasing scientific challenge and a massive economic need. This book presents thoroughly reviewed and revised full versions of papers presented at a workshop on the topic held during KDD'99 in San Diego, California, USA in August 1999 complemented by several invited chapters and a detailed introductory survey in order to provide complete coverage of the relevant issues. The contributions presented cover all major tasks in data mining including parallel and distributed mining frameworks, associations, sequences, clustering, and classification. All in all, the volume presents the state of the art in the young and dynamic field of parallel and distributed data mining methods. It will be a valuable source of reference for researchers and professionals.

Download or read book Mining Very Large Databases with Parallel Processing written by Alex A. Freitas and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Mining of Massive Datasets written by Jure Leskovec and published by Cambridge University Press. This book was released on 2014-11-13 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Download or read book Scaling Up Machine Learning written by Ron Bekkerman and published by Cambridge University Press. This book was released on 2012 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.

Download or read book High Performance Computing and Networking written by Marian Bubak and published by Springer Science & Business Media. This book was released on 2000-04-28 with total page 723 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on High-Performance Computing and Networking, HPCN Europe 2000, held in Amsterdam, The Netherlands, in May 2000. The 52 revised full papers presented together with 34 revised posters were carefully reviewed for inclusion in the book. The papers are organized in sections on problem solving environments, metacomputing, load balancing, numerical parallel algorithms, virtual enterprises and virtual laboratories, cooperation coordination, Web-based tools for tele-working, monitoring and performance, low-level algorithms, Java in HPCN, cluster computing, data analysis, and applications in a variety of fields.

Download or read book Parallel and Distributed Processing written by Jose Rolim and published by Springer. This book was released on 2003-06-26 with total page 667 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Acta Numerica 2001 Volume 10 written by Arieh Iserles and published by Cambridge University Press. This book was released on 2001-08-23 with total page 570 pages. Available in PDF, EPUB and Kindle. Book excerpt: An annual volume presenting substantive survey articles in numerical analysis and scientific computing.

Download or read book Proceedings of the Fourth SIAM International Conference on Data Mining written by Michael W. Berry and published by SIAM. This book was released on 2004-01-01 with total page 556 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fourth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. This is reflected in the talks by the four keynote speakers who discuss data usability issues in systems for data mining in science and engineering, issues raised by new technologies that generate biological data, ways to find complex structured patterns in linked data, and advances in Bayesian inference techniques. This proceedings includes 61 research papers.

Download or read book Large Scale Data Analytics written by Aris Gkoulalas-Divanis and published by Springer Science & Business Media. This book was released on 2014-01-08 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book collects state-of-the-art research related to large-scale data analytics that has been accomplished over the last few years. This is among the first books devoted to this important area based on contributions from diverse scientific areas such as databases, data mining, supercomputing, hardware architecture, data visualization, statistics, and privacy. There is increasing need for new approaches and technologies that can analyze and synthesize very large amounts of data, in the order of petabytes, that are generated by massively distributed data sources. This requires new distributed architectures for data analysis. Additionally, the heterogeneity of such sources imposes significant challenges for the efficient analysis of the data under numerous constraints, including consistent data integration, data homogenization and scaling, privacy and security preservation. The authors also broaden reader understanding of emerging real-world applications in domains such as customer behavior modeling, graph mining, telecommunications, cyber-security, and social network analysis, all of which impose extra requirements for large-scale data analysis. Large-Scale Data Analytics is organized in 8 chapters, each providing a survey of an important direction of large-scale data analytics or individual results of the emerging research in the field. The book presents key recent research that will help shape the future of large-scale data analytics, leading the way to the design of new approaches and technologies that can analyze and synthesize very large amounts of heterogeneous data. Students, researchers, professionals and practitioners will find this book an authoritative and comprehensive resource.

Download or read book Data Mining in Large Sets of Complex Data written by Robson Leonardo Ferreira Cordeiro and published by Springer Science & Business Media. This book was released on 2013-01-11 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation? Can it be made automatically? Based on the work discussed in this book, the answers to both questions are a sound “yes”, and the results can be obtained in just minutes. In fact, results that used to require days or weeks of hard work from human specialists can now be obtained in minutes with high precision. Data Mining in Large Sets of Complex Data discusses new algorithms that take steps forward from traditional data mining (especially for clustering) by considering large, complex datasets. Usually, other works focus in one aspect, either data size or complexity. This work considers both: it enables mining complex data from high impact applications, such as breast cancer diagnosis, region classification in satellite images, assistance to climate change forecast, recommendation systems for the Web and social networks; the data are large in the Terabyte-scale, not in Giga as usual; and very accurate results are found in just minutes. Thus, it provides a crucial and well timed contribution for allowing the creation of real time applications that deal with Big Data of high complexity in which mining on the fly can make an immeasurable difference, such as supporting cancer diagnosis or detecting deforestation.

Download or read book Big Data Analytics in HIV AIDS Research written by Al Mazari, Ali and published by IGI Global. This book was released on 2018-04-27 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the advent of new technologies in big data science, the study of medical problems has made significant progress. Connecting medical studies and computational methods is crucial for the advancement of the medical industry. Big Data Analytics in HIV/AIDS Research provides emerging research on the development and implementation of computational techniques in big data analysis for biological and medical practices. While highlighting topics such as deep learning, management software, and molecular modeling, this publication explores the various applications of data analysis in clinical decision making. This book is a vital resource for medical practitioners, nurses, scientists, researchers, and students seeking current research on the connections between data analytics in the field of medicine.

Download or read book Research Anthology on Big Data Analytics Architectures and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-09-24 with total page 1988 pages. Available in PDF, EPUB and Kindle. Book excerpt: Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.

Download or read book Partitional Clustering Algorithms written by M. Emre Celebi and published by Springer. This book was released on 2014-11-07 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Next Generation of Data Mining written by Hillol Kargupta and published by CRC Press. This book was released on 2008-12-24 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drawn from the US National Science Foundation's Symposium on Next Generation of Data Mining and Cyber-Enabled Discovery for Innovation (NGDM 07), Next Generation of Data Mining explores emerging technologies and applications in data mining as well as potential challenges faced by the field.Gathering perspectives from top experts across different di

Download or read book Parallel Processing for Artificial Intelligence 1 written by L.N. Kanal and published by Elsevier. This book was released on 2014-06-28 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence.Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.

Download or read book Rough Sets and Current Trends in Computing written by James J. Alpigini and published by Springer. This book was released on 2003-08-03 with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers selected for presentation at the Third Inter- tional Conference on Rough Sets and Current Trends in Computing (RSCTC 2002) held at Penn State Great Valley, Malvern, Pennsylvania, U.S.A., 14–16 October 2002. Rough set theoryand its applications constitute a branch of soft computing that has exhibited a signi?cant growth rate during recent years. RSCTC 2002 provided a forum for exchanging ideas among manyresearchers in the rough set communityand in various areas of soft computing and served as a stimulus for mutual understanding and cooperation. In recent years, there have been a number of advances in rough set theoryand applications. Hence, we have witnessed a growing number of international workshops on rough sets and their applications. In addition, it should be observed that one of the beauties of rough sets and the rough set philosophyis that it tends to complement and reinforce research in manytraditional research areas and applications. This is the main reason that manyinternational conferences are now including rough sets into the list of topics.