Fuzzy Systems and Data Mining VI
Fuzzy Systems and Data Mining VI

Author: A.J. Tallón-Ballesteros

Publisher: IOS Press

Published: 2020-11-13

Total Pages: 812

ISBN-13: 1643681354

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The interdisciplinary field of fuzzy logic encompass applications in the electrical, industrial, chemical and engineering realms as well as in areas of management and environmental issues, while data mining covers new approaches to big data, massive data, and scalable, parallel and distributed algorithms. This book presents papers from the 6th International Conference on Fuzzy Systems and Data Mining (FSDM 2020). The conference was originally due to be held from 13-16 November 2020 in Xiamen, China, but was changed to an online conference held on the same dates due to ongoing restrictions connected with the COVID-19 pandemic. The annual FSDM conference provides a platform for knowledge exchange between international experts, researchers academics and delegates from industry. This year, the committee received 316 submissions, of which 76 papers were selected for inclusion in the conference; an acceptance rate of 24%. The conference covers four main areas: fuzzy theory; algorithms and systems, which includes topics like stability; foundations and control; and fuzzy applications, which are widely used and cover various types of processing as well as hardware and architecture for big data and time series. Providing a current overview of research and developments in fuzzy logic and data mining, the book will be of interest to all those working in the field of data science.

Data Mining in E-learning
Data Mining in E-learning

Author: Cristobal Romero

Publisher: WIT Press

Published: 2006

Total Pages: 329

ISBN-13: 1845641523

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The development of e-learning systems, particularly, web-based education systems, has increased exponentially in recent years. Following this line, one of the most promising areas is the application of knowledge extraction. As one of the first of its kind, this book presents an introduction to e-learning systems, data mining concepts and the interaction between both areas.

Data Mining III
Data Mining III

Author: A. Zanasi

Publisher: WIT Press (UK)

Published: 2002

Total Pages: 1042

ISBN-13:

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Data mining brings together techniques from machine learning, pattern recognition, statistics, databases, linguistics and visualization in order to extract information from large databases. Originally principally concerned with behavioural applications, such as the understanding of customer behaviour, its scope has now been widened with the introduction of Text Mining techniques. Areas now encompassed by data mining include military, market, and competitive intelligence applications, taxonomies and internet search techniques, and knowledge management applications.

Data Mining IV
Data Mining IV

Author: Nelson F. F. Ebecken

Publisher: WIT Press (UK)

Published: 2004

Total Pages: 696

ISBN-13:

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Sixty-three papers from a December 2003 conference describe recent advances in data mining problems, encompassing both original research results and practical development experience. The goal is to develop algorithms and data structures that facilitate analysis of large amounts of data. Contributors from academia and industry cover such diverse areas as machine learning, databases, statistics, knowledge acquisitions, data visualization, and knowledge-based systems. Papers are organized in sections on data and text mining, clustering, categorization, CRM, case studies, post-processing and knowledge evaluation, genomics and bioinformatics, novel applications, and scalable algorithms and high- performance platforms. There is no subject index. The US office of WIT Press is Computational Mechanics. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com).

Mining of Massive Datasets
Mining of Massive Datasets

Author: Jure Leskovec

Publisher: Cambridge University Press

Published: 2014-11-13

Total Pages: 480

ISBN-13: 1107077230

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Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Fuzzy Systems and Data Mining V
Fuzzy Systems and Data Mining V

Author: A.J. Tallón-Ballesteros

Publisher: IOS Press

Published: 2019-11-06

Total Pages: 1186

ISBN-13: 1643680196

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The Fuzzy Systems and Data Mining (FSDM) conference is an annual event encompassing four main themes: fuzzy theory, algorithms and systems, which includes topics like stability, foundations and control; fuzzy application, which covers different kinds of processing as well as hardware and architectures for big data and time series and has wide applicability; the interdisciplinary field of fuzzy logic and data mining, encompassing applications in electrical, industrial, chemical and engineering fields as well as management and environmental issues; and data mining, outlining new approaches to big data, massive data, scalable, parallel and distributed algorithms. The annual conference provides a platform for knowledge exchange between international experts, researchers, academics and delegates from industry. This book includes the papers accepted and presented at the 5th International Conference on Fuzzy Systems and Data Mining (FSDM 2019), held in Kitakyushu, Japan on 18-21 October 2019. This year, FSDM received 442 submissions. All papers were carefully reviewed by program committee members, taking account of the quality, novelty, soundness, breadth and depth of the research topics falling within the scope of FSDM. The committee finally decided to accept 137 papers, which represents an acceptance rate of about 30%. The papers presented here are arranged in two sections: Fuzzy Sets and Data Mining, and Communications and Networks. Providing an overview of the most recent scientific and technological advances in the fields of fuzzy systems and data mining, the book will be of interest to all those working in these fields.

Data Mining Techniques
Data Mining Techniques

Author: Michael J. A. Berry

Publisher: John Wiley & Sons

Published: 2004-04-09

Total Pages: 671

ISBN-13: 0471470643

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Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information.

Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques

Author: Jiawei Han

Publisher: Elsevier

Published: 2011-06-09

Total Pages: 740

ISBN-13: 0123814804

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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

Data Mining in Dynamic Social Networks and Fuzzy Systems
Data Mining in Dynamic Social Networks and Fuzzy Systems

Author: Bhatnagar, Vishal

Publisher: IGI Global

Published: 2013-06-30

Total Pages: 412

ISBN-13: 1466642149

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Many organizations, whether in the public or private sector, have begun to take advantage of the tools and techniques used for data mining. Utilizing data mining tools, these organizations are able to reveal the hidden and unknown information from available data. Data Mining in Dynamic Social Networks and Fuzzy Systems brings together research on the latest trends and patterns of data mining tools and techniques in dynamic social networks and fuzzy systems. With these improved modern techniques of data mining, this publication aims to provide insight and support to researchers and professionals concerned with the management of expertise, knowledge, information, and organizational development.

Data Mining
Data Mining

Author: Yong Yin

Publisher: Springer Science & Business Media

Published: 2011-03-16

Total Pages: 320

ISBN-13: 184996338X

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Data Mining introduces in clear and simple ways how to use existing data mining methods to obtain effective solutions for a variety of management and engineering design problems. Data Mining is organised into two parts: the first provides a focused introduction to data mining and the second goes into greater depth on subjects such as customer analysis. It covers almost all managerial activities of a company, including: • supply chain design, • product development, • manufacturing system design, • product quality control, and • preservation of privacy. Incorporating recent developments of data mining that have made it possible to deal with management and engineering design problems with greater efficiency and efficacy, Data Mining presents a number of state-of-the-art topics. It will be an informative source of information for researchers, but will also be a useful reference work for industrial and managerial practitioners.