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Book Data Mining and Knowledge Discovery in Real Life Applications

Download or read book Data Mining and Knowledge Discovery in Real Life Applications written by Julio Ponce and published by BoD – Books on Demand. This book was released on 2009-01-01 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.

Book Data Mining and Knowledge Discovery via Logic Based Methods

Download or read book Data Mining and Knowledge Discovery via Logic Based Methods written by Evangelos Triantaphyllou and published by Springer Science & Business Media. This book was released on 2010-06-08 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: The importance of having ef cient and effective methods for data mining and kn- ledge discovery (DM&KD), to which the present book is devoted, grows every day and numerous such methods have been developed in recent decades. There exists a great variety of different settings for the main problem studied by data mining and knowledge discovery, and it seems that a very popular one is formulated in terms of binary attributes. In this setting, states of nature of the application area under consideration are described by Boolean vectors de ned on some attributes. That is, by data points de ned in the Boolean space of the attributes. It is postulated that there exists a partition of this space into two classes, which should be inferred as patterns on the attributes when only several data points are known, the so-called positive and negative training examples. The main problem in DM&KD is de ned as nding rules for recognizing (cl- sifying) new data points of unknown class, i. e. , deciding which of them are positive and which are negative. In other words, to infer the binary value of one more attribute, called the goal or class attribute. To solve this problem, some methods have been suggested which construct a Boolean function separating the two given sets of positive and negative training data points.

Book Practical Applications of Data Mining

Download or read book Practical Applications of Data Mining written by Sang Suh and published by Jones & Bartlett Publishers. This book was released on 2012 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.

Book Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques

Download or read book Data Mining and Knowledge Discovery Approaches Based on Rule Induction Techniques written by Evangelos Triantaphyllou and published by Springer Science & Business Media. This book was released on 2006-09-10 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines the core theory and practice of data mining and knowledge discovery (DM & KD) examining theoretical foundations for various methods, and presenting an array of examples, many drawn from real-life applications. Most theoretical developments are accompanied by extensive empirical analysis, offering a deep insight into both theoretical and practical aspects of the subject. The book presents the combined research experiences of 40 expert contributors of world renown.

Book Knowledge Discovery from Data Streams

Download or read book Knowledge Discovery from Data Streams written by Joao Gama and published by CRC Press. This book was released on 2010-05-25 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents

Book Handbook of Data Mining and Knowledge Discovery

Download or read book Handbook of Data Mining and Knowledge Discovery written by Jan M. Żytkow and published by Oxford University Press, USA. This book was released on 2002 with total page 1026 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining, or knowledge discovery in databases (KDD), is one of the fastest growing areas in computing application: it offers powerful tools to analyze the many large data bases used in business, science, and industry. Data mining technology searches large databases to extract information and patterns that can be translated into useful applications, such as classifying or predicting customer behavior. This book brings together fundamental knowledge on all aspects of data mining--concepts, theory, techniques, applications, and case studies. Designed for students and professionals in such fields as computing applications, information systems management and strategic research and management, the Handbook is a comprehensive guide to essential tools and technology, from neural networks to artificial intelligence. There is a strong emphasis on real-world case studies in such areas as banking, finance, marketing management, real estate, engineering, medicine, pharmacology, and the biosciences. A much needed resource on one of the fastest growing areas of computer applications--the development and use of tools to analyze, interpret, and make use of the enormous amounts of information stored in the world's databases.

Book Knowledge Discovery Practices and Emerging Applications of Data Mining  Trends and New Domains

Download or read book Knowledge Discovery Practices and Emerging Applications of Data Mining Trends and New Domains written by Kumar, A.V. Senthil and published by IGI Global. This book was released on 2010-08-31 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains introduces the reader to recent research activities in the field of data mining. This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, while promoting understanding and implementation of data mining techniques in emerging domains.

Book Industrial Applications of Machine Learning

Download or read book Industrial Applications of Machine Learning written by Pedro Larrañaga and published by CRC Press. This book was released on 2018-12-12 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka

Book Urban Informatics

    Book Details:
  • Author : Wenzhong Shi
  • Publisher : Springer Nature
  • Release : 2021-04-06
  • ISBN : 9811589836
  • Pages : 941 pages

Download or read book Urban Informatics written by Wenzhong Shi and published by Springer Nature. This book was released on 2021-04-06 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.

Book Data Mining with R

Download or read book Data Mining with R written by Luis Torgo and published by CRC Press. This book was released on 2016-11-30 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, including a new chapter that provides an introduction to data mining, to complement the already existing introduction to R. The second part includes case studies, and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies, and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book’s web site. These files include all the code used in the case studies, and they facilitate the "do-it-yourself" approach followed in the book. Designed for users of data analysis tools, as well as researchers and developers, the book should be useful for anyone interested in entering the "world" of R and data mining. About the Author Luís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business’ MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA.

Book Data Warehousing and Knowledge Discovery

Download or read book Data Warehousing and Knowledge Discovery written by Yahiko Kambayashi and published by Springer Science & Business Media. This book was released on 2000-08-25 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Second International Conference on Data Warehousing and Knowledge Discovery (DaWaK 2000) was held in Greenwich, UK 4–6 September. DaWaK 2000 was a forum where researchers from data warehousing and knowledge discovery disciplines could exchange ideas on improving next generation decision support and data mining systems. The conference focused on the logical and physical design of data warehousing and knowledge discovery systems. The scope of the papers covered the most recent and relevant topics in the areas of data warehousing, multidimensional databases, OLAP, knowledge discovery and mining complex databases. These proceedings contain the technical papers selected for presentation at the conference. We received more than 90 papers from over 20 countries and the program committee finally selected 31 long papers and 11 short papers. The conference program included three invited talks, namely, “A Foolish Consistency: Technical Challenges in Consistency Management” by Professor Anthony Finkelstein, University College London, UK; “European Plan for Research in Data Warehousing and Knowledge Discovery” by Dr. Harald Sonnberger (Head of Unit A4, Eurostat, European Commission); and “Security in Data Warehousing” by Professor Bharat Bhargava, Purdue University, USA.

Book Knowledge Discovery and Data Mining  Current Issues and New Applications

Download or read book Knowledge Discovery and Data Mining Current Issues and New Applications written by Takao Terano and published by Springer Science & Business Media. This book was released on 2007-07-13 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Fourth Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2000) was held at the Keihanna-Plaza, Kyoto, Japan, April 18 - 20, 2000. PAKDD 2000 provided an international forum for researchers and applica tion developers to share their original research results and practical development experiences. A wide range of current KDD topics were covered including ma chine learning, databases, statistics, knowledge acquisition, data visualization, knowledge-based systems, soft computing, and high performance computing. It followed the success of PAKDD 97 in Singapore, PAKDD 98 in Austraha, and PAKDD 99 in China by bringing together participants from universities, indus try, and government from all over the world to exchange problems and challenges and to disseminate the recently developed KDD techniques. This PAKDD 2000 proceedings volume addresses both current issues and novel approaches in regards to theory, methodology, and real world application. The technical sessions were organized according to subtopics such as Data Mining Theory, Feature Selection and Transformation, Clustering, Application of Data Mining, Association Rules, Induction, Text Mining, Web and Graph Mining. Of the 116 worldwide submissions, 33 regular papers and 16 short papers were accepted for presentation at the conference and included in this volume. Each submission was critically reviewed by two to four program committee members based on their relevance, originality, quality, and clarity.

Book Advanced Techniques in Knowledge Discovery and Data Mining

Download or read book Advanced Techniques in Knowledge Discovery and Data Mining written by Nikhil Pal and published by Springer. This book was released on 2005-07-01 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.

Book Padd97

    Book Details:
  • Author : International Conference on the Practical Application of Knowledge Discovery and Data Mining
  • Publisher :
  • Release : 1997-04-01
  • ISBN : 9780952555476
  • Pages : 301 pages

Download or read book Padd97 written by International Conference on the Practical Application of Knowledge Discovery and Data Mining and published by . This book was released on 1997-04-01 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Data Mining and Knowledge Discovery for Geoscientists

Download or read book Data Mining and Knowledge Discovery for Geoscientists written by Guangren Shi and published by Elsevier. This book was released on 2013-10-09 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: Currently there are major challenges in data mining applications in the geosciences. This is due primarily to the fact that there is a wealth of available mining data amid an absence of the knowledge and expertise necessary to analyze and accurately interpret the same data. Most geoscientists have no practical knowledge or experience using data mining techniques. For the few that do, they typically lack expertise in using data mining software and in selecting the most appropriate algorithms for a given application. This leads to a paradoxical scenario of "rich data but poor knowledge". The true solution is to apply data mining techniques in geosciences databases and to modify these techniques for practical applications. Authored by a global thought leader in data mining, Data Mining and Knowledge Discovery for Geoscientists addresses these challenges by summarizing the latest developments in geosciences data mining and arming scientists with the ability to apply key concepts to effectively analyze and interpret vast amounts of critical information. - Focuses on 22 of data mining's most practical algorithms and popular application samples - Features 36 case studies and end-of-chapter exercises unique to the geosciences to underscore key data mining applications - Presents a practical and integrated system of data mining and knowledge discovery for geoscientists - Rigorous yet broadly accessible to geoscientists, engineers, researchers and programmers in data mining - Introduces widely used algorithms, their basic principles and conditions of applications, diverse case studies, and suggests algorithms that may be suitable for specific applications

Book Soft Computing for Knowledge Discovery and Data Mining

Download or read book Soft Computing for Knowledge Discovery and Data Mining written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2007-10-25 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining is the science and technology of exploring large and complex bodies of data in order to discover useful patterns. It is extremely important because it enables modeling and knowledge extraction from abundant data availability. This book introduces soft computing methods extending the envelope of problems that data mining can solve efficiently. It presents practical soft-computing approaches in data mining and includes various real-world case studies with detailed results.

Book Advances in Data Mining Knowledge Discovery and Applications

Download or read book Advances in Data Mining Knowledge Discovery and Applications written by Adem Karahoca and published by BoD – Books on Demand. This book was released on 2012-09-12 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Data Mining Knowledge Discovery and Applications aims to help data miners, researchers, scholars, and PhD students who wish to apply data mining techniques. The primary contribution of this book is highlighting frontier fields and implementations of the knowledge discovery and data mining. It seems to be same things are repeated again. But in general, same approach and techniques may help us in different fields and expertise areas. This book presents knowledge discovery and data mining applications in two different sections. As known that, data mining covers areas of statistics, machine learning, data management and databases, pattern recognition, artificial intelligence, and other areas. In this book, most of the areas are covered with different data mining applications. The eighteen chapters have been classified in two parts: Knowledge Discovery and Data Mining Applications.