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Data To Knowledge


Data To Knowledge
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Discovering Knowledge In Data


Discovering Knowledge In Data
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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.



Dama Dmbok


Dama Dmbok
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Author : Dama International
language : en
Publisher:
Release Date : 2017

Dama Dmbok written by Dama International and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Database management categories.


Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.



The Dama Dictionary Of Data Management


The Dama Dictionary Of Data Management
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Author : Dama International
language : en
Publisher:
Release Date : 2011

The Dama Dictionary Of Data Management written by Dama International and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Business & Economics categories.


A glossary of over 2,000 terms which provides a common data management vocabulary for IT and Business professionals, and is a companion to the DAMA Data Management Body of Knowledge (DAMA-DMBOK). Topics include: Analytics & Data Mining Architecture Artificial Intelligence Business Analysis DAMA & Professional Development Databases & Database Design Database Administration Data Governance & Stewardship Data Management Data Modeling Data Movement & Integration Data Quality Management Data Security Management Data Warehousing & Business Intelligence Document, Record & Content Management Finance & Accounting Geospatial Data Knowledge Management Marketing & Customer Relationship Management Meta-Data Management Multi-dimensional & OLAP Normalization Object-Orientation Parallel Database Processing Planning Process Management Project Management Reference & Master Data Management Semantic Modeling Software Development Standards Organizations Structured Query Language (SQL) XML Development



Data Mining


Data Mining
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Author : Krzysztof J. Cios
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-05

Data Mining written by Krzysztof J. Cios 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 2007-10-05 with Computers categories.


“If you torture the data long enough, Nature will confess,” said 1991 Nobel-winning economist Ronald Coase. The statement is still true. However, achieving this lofty goal is not easy. First, “long enough” may, in practice, be “too long” in many applications and thus unacceptable. Second, to get “confession” from large data sets one needs to use state-of-the-art “torturing” tools. Third, Nature is very stubborn — not yielding easily or unwilling to reveal its secrets at all. Fortunately, while being aware of the above facts, the reader (a data miner) will find several efficient data mining tools described in this excellent book. The book discusses various issues connecting the whole spectrum of approaches, methods, techniques and algorithms falling under the umbrella of data mining. It starts with data understanding and preprocessing, then goes through a set of methods for supervised and unsupervised learning, and concludes with model assessment, data security and privacy issues. It is this specific approach of using the knowledge discovery process that makes this book a rare one indeed, and thus an indispensable addition to many other books on data mining. To be more precise, this is a book on knowledge discovery from data. As for the data sets, the easy-to-make statement is that there is no part of modern human activity left untouched by both the need and the desire to collect data. The consequence of such a state of affairs is obvious.



Feature Selection For Knowledge Discovery And Data Mining


Feature Selection For Knowledge Discovery And Data Mining
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Author : Huan Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Feature Selection For Knowledge Discovery And Data Mining written by Huan Liu 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 2012-12-06 with Computers categories.


As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.



Open Data And The Knowledge Society


Open Data And The Knowledge Society
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Author : Bridgette Wessels
language : en
Publisher:
Release Date : 2017

Open Data And The Knowledge Society written by Bridgette Wessels and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Information society categories.


While there is a lot of talk about how we now live in a knowledge society, the reality has been less impressive: we have yet to truly transition to a knowledge society--in part, this book argues, because discussion mostly focuses on a knowledge economy and information society rather than on ways to mobilize to create an actual knowledge society. That all may change, however, with the rise of open data and big data. This book considers the role of the open data movement in fostering transformation, showing that at the heart of any successful mobilization will be an emerging open data ecosystem and new ways for societal actors to effectively produce and use data.



Knowledge Discovery In Big Data From Astronomy And Earth Observation


Knowledge Discovery In Big Data From Astronomy And Earth Observation
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Author : Petr Skoda
language : en
Publisher: Elsevier
Release Date : 2020-04-09

Knowledge Discovery In Big Data From Astronomy And Earth Observation written by Petr Skoda and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-09 with Computers categories.


Knowledge Discovery in Big Data from Astronomy and Earth Observation: Astrogeoinformatics bridges the gap between astronomy and geoscience in the context of applications, techniques and key principles of big data. Machine learning and parallel computing are increasingly becoming cross-disciplinary as the phenomena of Big Data is becoming common place. This book provides insight into the common workflows and data science tools used for big data in astronomy and geoscience. After establishing similarity in data gathering, pre-processing and handling, the data science aspects are illustrated in the context of both fields. Software, hardware and algorithms of big data are addressed. Finally, the book offers insight into the emerging science which combines data and expertise from both fields in studying the effect of cosmos on the earth and its inhabitants.



Big Data And Knowledge Sharing In Virtual Organizations


Big Data And Knowledge Sharing In Virtual Organizations
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Author : Gyamfi, Albert
language : en
Publisher: IGI Global
Release Date : 2019-01-25

Big Data And Knowledge Sharing In Virtual Organizations written by Gyamfi, Albert and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-01-25 with Computers categories.


Knowledge in its pure state is tacit in nature—difficult to formalize and communicate—but can be converted into codified form and shared through both social interactions and the use of IT-based applications and systems. Even though there seems to be considerable synergies between the resulting huge data and the convertible knowledge, there is still a debate on how the increasing amount of data captured by corporations could improve decision making and foster innovation through effective knowledge-sharing practices. Big Data and Knowledge Sharing in Virtual Organizations provides innovative insights into the influence of big data analytics and artificial intelligence and the tools, methods, and techniques for knowledge-sharing processes in virtual organizations. The content within this publication examines cloud computing, machine learning, and knowledge sharing. It is designed for government officials and organizations, policymakers, academicians, researchers, technology developers, and students.



Theory Of Knowledge Structures And Processes


Theory Of Knowledge Structures And Processes
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Author : Mark Burgin
language : en
Publisher: World Scientific
Release Date : 2016-10-27

Theory Of Knowledge Structures And Processes written by Mark Burgin and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-27 with Business & Economics categories.


This book aims to synthesize different directions in knowledge studies into a unified theory of knowledge and knowledge processes. It explicates important relations between knowledge and information. It provides the readers with understanding of the essence and structure of knowledge, explicating operations and process that are based on knowledge and vital for society.The book also highlights how the theory of knowledge paves the way for more advanced design and utilization of computers and networks.



Human Computer Interaction And Knowledge Discovery In Complex Unstructured Big Data


Human Computer Interaction And Knowledge Discovery In Complex Unstructured Big Data
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2013-06-26

Human Computer Interaction And Knowledge Discovery In Complex Unstructured Big Data written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-26 with Computers categories.


This book constitutes the refereed proceedings of the Third Workshop on Human-Computer Interaction and Knowledge Discovery, HCI-KDD 2013, held in Maribor, Slovenia, in July 2013, at SouthCHI 2013. The 20 revised papers presented were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections on human-computer interaction and knowledge discovery, knowledge discovery and smart homes, smart learning environments, and visualization data analytics.