Advanced Methods For Knowledge Discovery From Complex Data

Advanced Methods For Knowledge Discovery From Complex Data Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Advanced Methods For Knowledge Discovery From Complex Data book. This book definitely worth reading, it is an incredibly well-written.

Advanced Methods for Knowledge Discovery from Complex Data

Author : Ujjwal Maulik,Lawrence B. Holder,Diane J. Cook
Publisher : Springer Science & Business Media
Page : 375 pages
File Size : 48,5 Mb
Release : 2006-05-06
Category : Computers
ISBN : 9781846282843

Get Book

Advanced Methods for Knowledge Discovery from Complex Data by Ujjwal Maulik,Lawrence B. Holder,Diane J. Cook Pdf

The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the following chapters.

Advanced Methods for Knowledge Discovery from Complex Data

Author : Ujjwal Maulik,Lawrence B. Holder,Diane J. Cook
Publisher : Springer
Page : 0 pages
File Size : 42,5 Mb
Release : 2005-11-09
Category : Computers
ISBN : 1852339896

Get Book

Advanced Methods for Knowledge Discovery from Complex Data by Ujjwal Maulik,Lawrence B. Holder,Diane J. Cook Pdf

The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the followingchapters.

Data Science, Learning by Latent Structures, and Knowledge Discovery

Author : Berthold Lausen,Sabine Krolak-Schwerdt,Matthias Böhmer
Publisher : Springer
Page : 560 pages
File Size : 45,7 Mb
Release : 2015-05-06
Category : Mathematics
ISBN : 9783662449837

Get Book

Data Science, Learning by Latent Structures, and Knowledge Discovery by Berthold Lausen,Sabine Krolak-Schwerdt,Matthias Böhmer Pdf

This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.

Advanced Techniques in Knowledge Discovery and Data Mining

Author : Nikhil Pal
Publisher : Springer
Page : 0 pages
File Size : 51,6 Mb
Release : 2014-12-10
Category : Computers
ISBN : 1447157524

Get Book

Advanced Techniques in Knowledge Discovery and Data Mining by Nikhil Pal Pdf

Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.

Knowledge Discovery and Data Mining

Author : O. Maimon,M. Last
Publisher : Springer Science & Business Media
Page : 169 pages
File Size : 42,6 Mb
Release : 2013-03-09
Category : Computers
ISBN : 9781475732962

Get Book

Knowledge Discovery and Data Mining by O. Maimon,M. Last Pdf

This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).

Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications

Author : Nguyen, Tho Manh
Publisher : IGI Global
Page : 426 pages
File Size : 47,9 Mb
Release : 2009-07-31
Category : Education
ISBN : 9781605667492

Get Book

Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development: Innovative Methods and Applications by Nguyen, Tho Manh Pdf

Recently, researchers have focused on challenging problems facing the development of data warehousing, knowledge discovery, and data mining applications.

Advanced Methods for Inconsistent Knowledge Management

Author : Ngoc Thanh Nguyen
Publisher : Springer Science & Business Media
Page : 352 pages
File Size : 41,6 Mb
Release : 2007-09-12
Category : Business & Economics
ISBN : 9781846288890

Get Book

Advanced Methods for Inconsistent Knowledge Management by Ngoc Thanh Nguyen Pdf

This book is a first. It fills a major gap in the market and provides a wide snapshot of intelligent technologies for inconsistency resolution. The need for this resolution of knowledge inconsistency arises in many practical applications of computer systems. This kind of inconsistency results from the use of various resources of knowledge in realizing practical tasks. These resources are often autonomous and use different mechanisms for processing knowledge about the same real world. This can lead to compatibility problems.

Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development

Author : Tho Manh Nguyen
Publisher : IGI Global Snippet
Page : 403 pages
File Size : 40,9 Mb
Release : 2010
Category : Computers
ISBN : 160566748X

Get Book

Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development by Tho Manh Nguyen Pdf

"This book provides a comprehensive analysis on current issues and trends in retrieval expansion"--Provided by publisher.

Data Mining and Knowledge Discovery for Big Data

Author : Wesley W. Chu
Publisher : Springer Science & Business Media
Page : 311 pages
File Size : 43,9 Mb
Release : 2013-09-24
Category : Technology & Engineering
ISBN : 9783642408373

Get Book

Data Mining and Knowledge Discovery for Big Data by Wesley W. Chu Pdf

The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for patterns in complex structural information. In biomedicine for example, modeling complex biological systems requires linking knowledge across many levels of science, from genes to disease. Further, the data characteristics of the problems have also grown from static to dynamic and spatiotemporal, complete to incomplete, and centralized to distributed, and grow in their scope and size (this is known as big data). The effective integration of big data for decision-making also requires privacy preservation. The contributions to this monograph summarize the advances of data mining in the respective fields. This volume consists of nine chapters that address subjects ranging from mining data from opinion, spatiotemporal databases, discriminative subgraph patterns, path knowledge discovery, social media, and privacy issues to the subject of computation reduction via binary matrix factorization.

Decomposition Methodology for Knowledge Discovery and Data Mining

Author : Oded Maimon,Lior Rokach
Publisher : World Scientific Publishing Company
Page : 344 pages
File Size : 42,8 Mb
Release : 2005-05-30
Category : Computers
ISBN : 9789813106444

Get Book

Decomposition Methodology for Knowledge Discovery and Data Mining by Oded Maimon,Lior Rokach Pdf

Data Mining is the science and technology of exploring data in order to discover previously unknown patterns. It is a part of the overall process of Knowledge Discovery in Databases (KDD). The accessibility and abundance of information today makes data mining a matter of considerable importance and necessity. This book provides an introduction to the field with an emphasis on advanced decomposition methods in general data mining tasks and for classification tasks in particular. The book presents a complete methodology for decomposing classification problems into smaller and more manageable sub-problems that are solvable by using existing tools. The various elements are then joined together to solve the initial problem. The benefits of decomposition methodology in data mining include: increased performance (classification accuracy); conceptual simplification of the problem; enhanced feasibility for huge databases; clearer and more comprehensible results; reduced runtime by solving smaller problems and by using parallel/distributed computation; and the opportunity of using different techniques for individual sub-problems.

Data Mining and Knowledge Discovery Handbook

Author : Oded Maimon,Lior Rokach
Publisher : Springer Science & Business Media
Page : 1269 pages
File Size : 54,9 Mb
Release : 2010-09-10
Category : Computers
ISBN : 9780387098234

Get Book

Data Mining and Knowledge Discovery Handbook by Oded Maimon,Lior Rokach Pdf

This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

Knowledge Discovery in Multiple Databases

Author : Shichao Zhang,Chengqi Zhang,Xindong Wu
Publisher : Springer Science & Business Media
Page : 233 pages
File Size : 46,6 Mb
Release : 2012-12-06
Category : Computers
ISBN : 9780857293886

Get Book

Knowledge Discovery in Multiple Databases by Shichao Zhang,Chengqi Zhang,Xindong Wu Pdf

Many organizations have an urgent need of mining their multiple databases inherently distributed in branches (distributed data). In particular, as the Web is rapidly becoming an information flood, individuals and organizations can take into account low-cost information and knowledge on the Internet when making decisions. How to efficiently identify quality knowledge from different data sources has become a significant challenge. This challenge has attracted a great many researchers including the au thors who have developed a local pattern analysis, a new strategy for dis covering some kinds of potentially useful patterns that cannot be mined in traditional multi-database mining techniques. Local pattern analysis deliv ers high-performance pattern discovery from multiple databases. There has been considerable progress made on multi-database mining in such areas as hierarchical meta-learning, collective mining, database classification, and pe culiarity discovery. While these techniques continue to be future topics of interest concerning multi-database mining, this book focuses on these inter esting issues under the framework of local pattern analysis. The book is intended for researchers and students in data mining, dis tributed data analysis, machine learning, and anyone else who is interested in multi-database mining. It is also appropriate for use as a text supplement for broader courses that might also involve knowledge discovery in databases and data mining.

Data Mining - a search for knowledge

Author : Mohamed Rahama
Publisher : GRIN Verlag
Page : 26 pages
File Size : 45,5 Mb
Release : 2012-10-23
Category : Computers
ISBN : 9783656295204

Get Book

Data Mining - a search for knowledge by Mohamed Rahama Pdf

Essay from the year 2012 in the subject Computer Science - Theory, grade: B, ( Atlantic International University ) (School of Science and Engineering), course: Doctorate in Information Technology, language: English, abstract: Data mining is an independent science that based on advanced ways for information retrieval. Data mining is dealing with knowledge discovery in data warehouses without predefined hypotheses. So it is quite different from other applications such as decision support systems, OLAP and others which are looking for information on the factors and assumptions that we know it in advance. Data Mining supports multiple algorithms which have the ability to adopt automatic classification of historical data and predict future events. Data mining in the databases is designed to extract the hidden information, and it is a modern technology that imposed itself strongly in the information revolution, in the light of the great technological development and widespread use of data warehouses. Data mining techniques focus on building future forecasts and explore the behavior and trends, allowing a good estimation for right decisions that taken in a timely manner. This paper provides a general definition of data mining science and its most important techniques and algorithms used.

From Data and Information Analysis to Knowledge Engineering

Author : Myra Spiliopoulou,Rudolf Kruse,Christian Borgelt,Andreas Nürnberger,Wolfgang Gaul
Publisher : Springer Science & Business Media
Page : 788 pages
File Size : 51,5 Mb
Release : 2006-02-09
Category : Language Arts & Disciplines
ISBN : 3540313133

Get Book

From Data and Information Analysis to Knowledge Engineering by Myra Spiliopoulou,Rudolf Kruse,Christian Borgelt,Andreas Nürnberger,Wolfgang Gaul Pdf

This volume collects revised versions of papers presented at the 29th Annual Conference of the Gesellschaft für Klassifikation, the German Classification Society, held at the Otto-von-Guericke-University of Magdeburg, Germany, in March 2005. In addition to traditional subjects like Classification, Clustering, and Data Analysis, converage extends to a wide range of topics relating to Computer Science: Text Mining, Web Mining, Fuzzy Data Analysis, IT Security, Adaptivity and Personalization, and Visualization.

Knowledge Discovery in the Social Sciences

Author : Xiaoling Shu
Publisher : University of California Press
Page : 263 pages
File Size : 48,9 Mb
Release : 2020-02-04
Category : Social Science
ISBN : 9780520292307

Get Book

Knowledge Discovery in the Social Sciences by Xiaoling Shu Pdf

Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries