Mining Very Large Databases with Parallel Processing
Title | Mining Very Large Databases with Parallel Processing PDF eBook |
Author | Alex A. Freitas |
Publisher | Springer Science & Business Media |
Pages | 211 |
Release | 2012-12-06 |
Genre | Computers |
ISBN | 1461555213 |
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.
Large-Scale Parallel Data Mining
Title | Large-Scale Parallel Data Mining PDF eBook |
Author | Mohammed J. Zaki |
Publisher | Springer |
Pages | 270 |
Release | 2003-07-31 |
Genre | Computers |
ISBN | 3540465022 |
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.
Mining of Massive Datasets
Title | Mining of Massive Datasets PDF eBook |
Author | Jure Leskovec |
Publisher | Cambridge University Press |
Pages | 480 |
Release | 2014-11-13 |
Genre | Computers |
ISBN | 1107077230 |
Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.
Data Mining
Title | Data Mining PDF eBook |
Author | Bhavani Thuraisingham |
Publisher | CRC Press |
Pages | 292 |
Release | 2014-01-23 |
Genre | Business & Economics |
ISBN | 1482252503 |
Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges. Three parts divide Data Mining: Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision sup
Euro-Par’ 99 Parallel Processing
Title | Euro-Par’ 99 Parallel Processing PDF eBook |
Author | Patrick Amestoy |
Publisher | Springer |
Pages | 1503 |
Release | 2003-05-21 |
Genre | Computers |
ISBN | 354048311X |
Euro-Parisaninternationalconferencededicatedtothepromotionandadvan- ment of all aspects of parallel computing. The major themes can be divided into the broad categories of hardware, software, algorithms and applications for p- allel computing. The objective of Euro-Par is to provide a forum within which to promote the development of parallel computing both as an industrial te- nique and an academic discipline, extending the frontier of both the state of the art and the state of the practice. This is particularly important 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-Parareseenasresearchersinacademicdepartments,governmentlabora- ries and industrial organisations. Euro-Par’s objective is to become the primary choice of such professionals for the presentation of new results in their specic areas. Euro-Par is also interested in applications which demonstrate the e - tiveness of the main Euro-Par themes. There is now a permanent Web site for the series http://brahms. fmi. uni-passau. de/cl/europar where the history of the conference is described. Euro-Par is now sponsored by the Association of Computer Machinery and the International Federation of Information Processing. Euro-Par’99 The format of Euro-Par’99follows that of the past four conferences and consists of a number of topics eachindividually monitored by a committee of four. There were originally 23 topics for this year’s conference. The call for papers attracted 343 submissions of which 188 were accepted. Of the papers accepted, 4 were judged as distinguished, 111 as regular and 73 as short papers.
Data Mining and Knowledge Discovery with Evolutionary Algorithms
Title | Data Mining and Knowledge Discovery with Evolutionary Algorithms PDF eBook |
Author | Alex A. Freitas |
Publisher | Springer Science & Business Media |
Pages | 272 |
Release | 2013-11-11 |
Genre | Computers |
ISBN | 3662049236 |
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
Parallel Computing: Fundamentals And Applications - Proceedings Of The International Conference Parco99
Title | Parallel Computing: Fundamentals And Applications - Proceedings Of The International Conference Parco99 PDF eBook |
Author | Erik H D'hollander |
Publisher | World Scientific |
Pages | 788 |
Release | 2000-05-31 |
Genre | Computers |
ISBN | 1783261684 |
This millennium will see the increased use of parallel computing technologies at all levels of mainstream computing. Most computer hardware will use these technologies to achieve higher computing speeds, high speed access to very large distributed databases and greater flexibility through heterogeneous computing. These developments can be expected to result in the extended use of all types of parallel computers in virtually all areas of human endeavour. Compute-intensive problems in emerging areas such as financial modelling and multimedia systems, in addition to traditional application areas of parallel computing such as scientific computing and simulation, will stimulate the developments. Parallel computing as a field of scientific research and development will move from a niche concentrating on solving compute-intensive scientific and engineering problems to become one of the fundamental computing technologies.This book gives a retrospective view of what has been achieved in the parallel computing field during the past three decades, as well as a prospective view of expected future developments./a