Download or read book Advanced Methods for Knowledge Discovery from Complex Data written by Ujjwal Maulik and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Complex Data Warehousing and Knowledge Discovery for Advanced Retrieval Development Innovative Methods and Applications written by Nguyen, Tho Manh and published by IGI Global. This book was released on 2009-07-31 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, researchers have focused on challenging problems facing the development of data warehousing, knowledge discovery, and data mining applications.

Download or read book Advanced Methods for Inconsistent Knowledge Management written by Ngoc Thanh Nguyen and published by Springer Science & Business Media. This book was released on 2007-09-12 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Advanced Data Mining Techniques written by David L. Olson and published by Springer Science & Business Media. This book was released on 2008-01-01 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.

Download or read book Data Mining and Knowledge Discovery Handbook written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2010-09-10 with total page 1269 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Science Learning by Latent Structures and Knowledge Discovery written by Berthold Lausen and published by Springer. This book was released on 2015-05-06 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Mining and Knowledge Discovery Handbook written by Oded Maimon and published by Springer Science & Business Media. This book was released on 2006-05-28 with total page 1378 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Advanced Methods for Knowledge Discovery from Complex Data written by Ujjwal Maulik and published by Springer. This book was released on 2005-11-09 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book From Data and Information Analysis to Knowledge Engineering written by Myra Spiliopoulou and published by Springer Science & Business Media. This book was released on 2006-02-09 with total page 788 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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.

Download or read book Mathematical Methods for Knowledge Discovery and Data Mining written by Felici, Giovanni and published by IGI Global. This book was released on 2007-10-31 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book focuses on the mathematical models and methods that support most data mining applications and solution techniques, covering such topics as association rules; Bayesian methods; data visualization; kernel methods; neural networks; text, speech, and image recognition; an invaluable resource for scholars and practitioners in the fields of biomedicine, engineering, finance, manufacturing, marketing, performance measurement, and telecommunications"--Provided by publisher.

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

Download or read book Advanced Techniques in Knowledge Discovery and Data Mining written by Nikhil Pal and published by Springer Science & Business Media. This book was released on 2007-12-31 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: Clear and concise explanations to understand the learning paradigms. Chapters written by leading world experts.

Download or read book Feature Selection for Knowledge Discovery and Data Mining written by Huan Liu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Advanced Methodologies and Technologies in Network Architecture Mobile Computing and Data Analytics written by Khosrow-Pour, D.B.A., Mehdi and published by IGI Global. This book was released on 2018-10-19 with total page 1946 pages. Available in PDF, EPUB and Kindle. Book excerpt: From cloud computing to data analytics, society stores vast supplies of information through wireless networks and mobile computing. As organizations are becoming increasingly more wireless, ensuring the security and seamless function of electronic gadgets while creating a strong network is imperative. Advanced Methodologies and Technologies in Network Architecture, Mobile Computing, and Data Analytics highlights the challenges associated with creating a strong network architecture in a perpetually online society. Readers will learn various methods in building a seamless mobile computing option and the most effective means of analyzing big data. This book is an important resource for information technology professionals, software developers, data analysts, graduate-level students, researchers, computer engineers, and IT specialists seeking modern information on emerging methods in data mining, information technology, and wireless networks.

Download or read book Routledge International Handbook of Advanced Quantitative Methods in Nursing Research written by Susan J Henly and published by Routledge. This book was released on 2015-07-24 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to support global development of nursing science, the Routledge International Handbook of Advanced Quantitative Methods in Nursing Research provides a new, comprehensive, and authoritative treatment of advanced quantitative methods for nursing research. Incorporating past approaches that have served as the foundation for the science, this cutting edge book also explores emerging approaches that will shape its future. Divided into six parts, it covers: -the domain of nursing science - measurement—classical test theory, IRT, clinimetrics, behavioral observation, biophysical measurement -models for prediction and explanation—SEM, general growth mixture models, hierarchical models, analysis of dynamic systems -intervention research—theory-based interventions, causality, third variables, pilot studies, quasi-experimental design, joint models for longitudinal data and time to event -e-science—DIKW paradigm, big data, data mining, omics, FMRI -special topics—comparative effectiveness and meta-analysis, patient safety, economics research in nursing, mixed methods, global research dissemination Written by a distinguished group of international nursing scientists, scientists from related fields, and methodologists, the Handbook is the ideal reference for everyone involved in nursing science, whether they are graduate students, academics, editors and reviewers, or clinical investigators.

Download or read book Data Mining and Machine Learning written by Mohammed J. Zaki and published by Cambridge University Press. This book was released on 2020-01-30 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.