Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Foundations And Advances In Data Mining
Download Foundations And Advances In Data Mining full books in PDF, epub, and Kindle. Read online Foundations And Advances In Data Mining ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Foundations and Advances in Data Mining by : Wesley Chu
Download or read book Foundations and Advances in Data Mining written by Wesley Chu and published by Springer. This book was released on 2009-09-02 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
Book Synopsis Foundations and Advances in Data Mining by : Wesley Chu
Download or read book Foundations and Advances in Data Mining written by Wesley Chu and published by Springer Science & Business Media. This book was released on 2005-09-15 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this carefully edited volume a theoretical foundation as well as important new directions for data-mining research are presented. It brings together a set of well respected data mining theoreticians and researchers with practical data mining experiences. The presented theories will give data mining practitioners a scientific perspective in data mining and thus provide more insight into their problems, and the provided new data mining topics can be expected to stimulate further research in these important directions.
Book Synopsis Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends by : Taniar, David
Download or read book Exploring Advances in Interdisciplinary Data Mining and Analytics: New Trends written by Taniar, David and published by IGI Global. This book was released on 2011-12-31 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book is an updated look at the state of technology in the field of data mining and analytics offering the latest technological, analytical, ethical, and commercial perspectives on topics in data mining"--Provided by publisher.
Book Synopsis Statistical Data Analytics by : Walter W. Piegorsch
Download or read book Statistical Data Analytics written by Walter W. Piegorsch and published by John Wiley & Sons. This book was released on 2015-12-21 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others.
Book Synopsis Statistical Data Analytics by : Walter W. Piegorsch
Download or read book Statistical Data Analytics written by Walter W. Piegorsch and published by John Wiley & Sons. This book was released on 2015-06-11 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to statistical methods for data mining and knowledge discovery. Applications of data mining and ‘big data’ increasingly take center stage in our modern, knowledge-driven society, supported by advances in computing power, automated data acquisition, social media development and interactive, linkable internet software. This book presents a coherent, technical introduction to modern statistical learning and analytics, starting from the core foundations of statistics and probability. It includes an overview of probability and statistical distributions, basics of data manipulation and visualization, and the central components of standard statistical inferences. The majority of the text extends beyond these introductory topics, however, to supervised learning in linear regression, generalized linear models, and classification analytics. Finally, unsupervised learning via dimension reduction, cluster analysis, and market basket analysis are introduced. Extensive examples using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others. Statistical Data Analytics: Focuses on methods critically used in data mining and statistical informatics. Coherently describes the methods at an introductory level, with extensions to selected intermediate and advanced techniques. Provides informative, technical details for the highlighted methods. Employs the open-source R language as the computational vehicle – along with its burgeoning collection of online packages – to illustrate many of the analyses contained in the book. Concludes each chapter with a range of interesting and challenging homework exercises using actual data from a variety of informatic application areas. This book will appeal as a classroom or training text to intermediate and advanced undergraduates, and to beginning graduate students, with sufficient background in calculus and matrix algebra. It will also serve as a source-book on the foundations of statistical informatics and data analytics to practitioners who regularly apply statistical learning to their modern data.
Book Synopsis Data Mining: Foundations and Practice by : Tsau Young Lin
Download or read book Data Mining: Foundations and Practice written by Tsau Young Lin and published by Springer Science & Business Media. This book was released on 2008-08-20 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: The IEEE ICDM 2004 workshop on the Foundation of Data Mining and the IEEE ICDM 2005 workshop on the Foundation of Semantic Oriented Data and Web Mining focused on topics ranging from the foundations of data mining to new data mining paradigms. The workshops brought together both data mining researchers and practitioners to discuss these two topics while seeking solutions to long standing data mining problems and stimul- ing new data mining research directions. We feel that the papers presented at these workshops may encourage the study of data mining as a scienti?c ?eld and spark new communications and collaborations between researchers and practitioners. Toexpressthevisionsforgedintheworkshopstoawiderangeofdatam- ing researchers and practitioners and foster active participation in the study of foundations of data mining, we edited this volume by involving extended and updated versions of selected papers presented at those workshops as well as some other relevant contributions. The content of this book includes st- ies of foundations of data mining from theoretical, practical, algorithmical, and managerial perspectives. The following is a brief summary of the papers contained in this book.
Book Synopsis Foundations of Data Mining and Knowledge Discovery by : Tsau Young Lin
Download or read book Foundations of Data Mining and Knowledge Discovery written by Tsau Young Lin and published by Springer Science & Business Media. This book was released on 2005-09-02 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research. Data mining, which integrates various technologies, including computational intelligence, database and knowledge management, machine learning, soft computing, and statistics, is one of the fastest growing fields in computer science. Although many data mining techniques have been developed, further development of the field requires a close examination of its foundations. This volume presents the results of investigations into the foundations of the discipline, and represents the state of the art for much of the current research. This book will prove extremely valuable and fruitful for data mining researchers, no matter whether they would like to uncover the fundamental principles behind data mining, or apply the theories to practical applications.
Book Synopsis Privacy Preserving Data Mining by : Jaideep Vaidya
Download or read book Privacy Preserving Data Mining written by Jaideep Vaidya and published by Springer Science & Business Media. This book was released on 2006-09-28 with total page 124 pages. Available in PDF, EPUB and Kindle. Book excerpt: Privacy preserving data mining implies the "mining" of knowledge from distributed data without violating the privacy of the individual/corporations involved in contributing the data. This volume provides a comprehensive overview of available approaches, techniques and open problems in privacy preserving data mining. Crystallizing much of the underlying foundation, the book aims to inspire further research in this new and growing area. Privacy Preserving Data Mining is intended to be accessible to industry practitioners and policy makers, to help inform future decision making and legislation, and to serve as a useful technical reference.
Book Synopsis Data Mining: Foundations and Intelligent Paradigms by : Dawn E. Holmes
Download or read book Data Mining: Foundations and Intelligent Paradigms written by Dawn E. Holmes and published by Springer. This book was released on 2011-11-07 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Book Synopsis Scientific Data Mining and Knowledge Discovery by : Mohamed Medhat Gaber
Download or read book Scientific Data Mining and Knowledge Discovery written by Mohamed Medhat Gaber and published by Springer Science & Business Media. This book was released on 2009-09-19 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mohamed Medhat Gaber “It is not my aim to surprise or shock you – but the simplest way I can summarise is to say that there are now in the world machines that think, that learn and that create. Moreover, their ability to do these things is going to increase rapidly until – in a visible future – the range of problems they can handle will be coextensive with the range to which the human mind has been applied” by Herbert A. Simon (1916-2001) 1Overview This book suits both graduate students and researchers with a focus on discovering knowledge from scienti c data. The use of computational power for data analysis and knowledge discovery in scienti c disciplines has found its roots with the re- lution of high-performance computing systems. Computational science in physics, chemistry, and biology represents the rst step towards automation of data analysis tasks. The rational behind the developmentof computationalscience in different - eas was automating mathematical operations performed in those areas. There was no attention paid to the scienti c discovery process. Automated Scienti c Disc- ery (ASD) [1–3] represents the second natural step. ASD attempted to automate the process of theory discovery supported by studies in philosophy of science and cognitive sciences. Although early research articles have shown great successes, the area has not evolved due to many reasons. The most important reason was the lack of interaction between scientists and the automating systems.
Book Synopsis Advances in Data Mining by : Petra Perner
Download or read book Advances in Data Mining written by Petra Perner and published by Springer Science & Business Media. This book was released on 2002-08-21 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents six thoroughly reviewed and revised full papers describing selected projects on data mining. Three papers deal with data mining and e-commerce, focusing on sequence rule analysis, association rule mining and knowledge discovery in databases, and intelligent e-marketing with Web mining. One paper is devoted to experience management and process learning. The last two papers report on medical applications, namely on genomic data processing and on case-based reasoning for prognosis of influenza.
Book Synopsis Data Mining: Foundations and Intelligent Paradigms by : Dawn E. Holmes
Download or read book Data Mining: Foundations and Intelligent Paradigms written by Dawn E. Holmes and published by Springer. This book was released on 2011-11-07 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 2: Core Topics including Statistical, Time-Series and Bayesian Analysis” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.
Book Synopsis Web Usage Mining Techniques and Applications Across Industries by : Kumar, A.V. Senthil
Download or read book Web Usage Mining Techniques and Applications Across Industries written by Kumar, A.V. Senthil and published by IGI Global. This book was released on 2016-08-12 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Data Mining: Concepts and Techniques by : Jiawei Han
Download or read book Data Mining: Concepts and Techniques written by Jiawei Han and published by Elsevier. This book was released on 2011-06-09 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
Book Synopsis Advanced Data Mining and Applications by : Guojun Gan
Download or read book Advanced Data Mining and Applications written by Guojun Gan and published by Springer. This book was released on 2018-12-28 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 14th International Conference on Advanced Data Mining and Applications, ADMA 2018, held in Nanjing, China in November 2018. The 23 full and 22 short papers presented in this volume were carefully reviewed and selected from 104 submissions. The papers were organized in topical sections named: Data Mining Foundations; Big Data; Text and Multimedia Mining; Miscellaneous Topics.
Book Synopsis Advances in Knowledge Discovery and Data Mining by : Zhi-Hua Zhou
Download or read book Advances in Knowledge Discovery and Data Mining written by Zhi-Hua Zhou and published by Springer. This book was released on 2007-06-21 with total page 1161 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2007, held in Nanjing, China, May 2007. It covers new ideas, original research results and practical development experiences from all KDD-related areas including data mining, machine learning, data warehousing, data visualization, automatic scientific discovery, knowledge acquisition and knowledge-based systems.
Book Synopsis Foundations of Computational Intelligence by : Ajith Abraham
Download or read book Foundations of Computational Intelligence written by Ajith Abraham and published by Springer. This book was released on 2009-05-01 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Computational Intelligence Volume 6: Data Mining: Theoretical Foundations and Applications Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully in application areas such as bioinformatics, business, health care, banking, retail, and many others. Advanced representation schemes and computational intelligence techniques such as rough sets, neural networks; decision trees; fuzzy logic; evolutionary algorithms; arti- cial immune systems; swarm intelligence; reinforcement learning, association rule mining, Web intelligence paradigms etc. have proved valuable when they are - plied to Data Mining problems. Computational tools or solutions based on intel- gent systems are being used with great success in Data Mining applications. It is also observed that strong scientific advances have been made when issues from different research areas are integrated. This Volume comprises of 15 chapters including an overview chapter providing an up-to-date and state-of-the research on the applications of Computational Int- ligence techniques for Data Mining. The book is divided into 3 parts: Part-I: Data Click Streams and Temporal Data Mining Part-II: Text and Rule Mining Part-III: Applications Part I on Data Click Streams and Temporal Data Mining contains four chapters that describe several approaches in Data Click Streams and Temporal Data Mining.
