Knowledge Oriented Applications In Data Mining
DOWNLOAD
Download Knowledge Oriented Applications In Data Mining PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Knowledge Oriented Applications In Data Mining book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Knowledge Oriented Applications In Data Mining
DOWNLOAD
Author : Kimito Funatsu
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-01-21
Knowledge Oriented Applications In Data Mining written by Kimito Funatsu and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-21 with Computers categories.
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.
Knowledge Oriented Applications In Data Mining
DOWNLOAD
Author : Kimito Funatsu
language : en
Publisher: IntechOpen
Release Date : 2011-01-21
Knowledge Oriented Applications In Data Mining written by Kimito Funatsu and has been published by IntechOpen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-21 with Computers categories.
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by 'Data Mining' address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.
Data Mining And Medical Knowledge Management Cases And Applications
DOWNLOAD
Author : Berka, Petr
language : en
Publisher: IGI Global
Release Date : 2009-02-28
Data Mining And Medical Knowledge Management Cases And Applications written by Berka, Petr and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-02-28 with Computers categories.
The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.
Discovering Knowledge In Data
DOWNLOAD
Author : Daniel T. Larose
language : en
Publisher: John Wiley & Sons
Release Date : 2005-01-28
Discovering Knowledge In Data written by Daniel T. Larose and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-01-28 with Computers categories.
Learn Data Mining by doing data mining Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets. Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include: * Data preprocessing and classification * Exploratory analysis * Decision trees * Neural and Kohonen networks * Hierarchical and k-means clustering * Association rules * Model evaluation techniques Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge. An Instructor's Manual presenting detailed solutions to all the problems in the book is available online.
Educational Data Mining
DOWNLOAD
Author : Alejandro Peña-Ayala
language : en
Publisher: Springer
Release Date : 2013-11-08
Educational Data Mining written by Alejandro Peña-Ayala and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-08 with Technology & Engineering categories.
This book is devoted to the Educational Data Mining arena. It highlights works that show relevant proposals, developments, and achievements that shape trends and inspire future research. After a rigorous revision process sixteen manuscripts were accepted and organized into four parts as follows: · Profile: The first part embraces three chapters oriented to: 1) describe the nature of educational data mining (EDM); 2) describe how to pre-process raw data to facilitate data mining (DM); 3) explain how EDM supports government policies to enhance education. · Student modeling: The second part contains five chapters concerned with: 4) explore the factors having an impact on the student's academic success; 5) detect student's personality and behaviors in an educational game; 6) predict students performance to adjust content and strategies; 7) identify students who will most benefit from tutor support; 8) hypothesize the student answer correctness based on eye metrics and mouse click. · Assessment: The third part has four chapters related to: 9) analyze the coherence of student research proposals; 10) automatically generate tests based on competences; 11) recognize students activities and visualize these activities for being presented to teachers; 12) find the most dependent test items in students response data. · Trends: The fourth part encompasses four chapters about how to: 13) mine text for assessing students productions and supporting teachers; 14) scan student comments by statistical and text mining techniques; 15) sketch a social network analysis (SNA) to discover student behavior profiles and depict models about their collaboration; 16) evaluate the structure of interactions between the students in social networks. This volume will be a source of interest to researchers, practitioners, professors, and postgraduate students aimed at updating their knowledge and find targets for future work in the field of educational data mining.
Data Mining For Business Applications
DOWNLOAD
Author : Longbing Cao
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-03
Data Mining For Business Applications written by Longbing Cao and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-10-03 with Computers categories.
Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.
Practical Applications Of Data Mining
DOWNLOAD
Author : Sang Suh
language : en
Publisher: Jones & Bartlett Publishers
Release Date : 2012
Practical Applications Of Data Mining written by Sang Suh and has been published by Jones & Bartlett Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
Introduction to data mining -- Association rules -- Classification learning -- Statistics for data mining -- Rough sets and bayes theories -- Neural networks -- Clustering -- Fuzzy information retrieval.
Data Mining And Knowledge Discovery Handbook
DOWNLOAD
Author : Oded Maimon
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-28
Data Mining And Knowledge Discovery Handbook written by Oded Maimon and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-28 with Computers categories.
Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.
Applications Of Data Mining To Electronic Commerce
DOWNLOAD
Author : Ronny Kohavi
language : en
Publisher: Springer
Release Date : 2001-02-28
Applications Of Data Mining To Electronic Commerce written by Ronny Kohavi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001-02-28 with Business & Economics categories.
Applications of Data Mining to Electronic Commerce brings together in one place important contributions and up-to-date research results in this fast moving area. Applications of Data Mining to Electronic Commerce serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
New Fundamental Technologies In Data Mining
DOWNLOAD
Author : Kimito Funatsu
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-01-21
New Fundamental Technologies In Data Mining written by Kimito Funatsu and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-21 with Computers categories.
The progress of data mining technology and large public popularity establish a need for a comprehensive text on the subject. The series of books entitled by "Data Mining" address the need by presenting in-depth description of novel mining algorithms and many useful applications. In addition to understanding each section deeply, the two books present useful hints and strategies to solving problems in the following chapters. The contributing authors have highlighted many future research directions that will foster multi-disciplinary collaborations and hence will lead to significant development in the field of data mining.