Research And Trends In Data Mining Technologies And Applications

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Research and Trends in Data Mining Technologies and Applications

Author : Taniar, David
Publisher : IGI Global
Page : 340 pages
File Size : 47,8 Mb
Release : 2006-10-31
Category : Computers
ISBN : 9781599042732

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Research and Trends in Data Mining Technologies and Applications by Taniar, David Pdf

Activities in data warehousing and mining are constantly emerging. Data mining methods, algorithms, online analytical processes, data mart and practical issues consistently evolve, providing a challenge for professionals in the field. Research and Trends in Data Mining Technologies and Applications focuses on the integration between the fields of data warehousing and data mining, with emphasis on the applicability to real-world problems. This book provides an international perspective, highlighting solutions to some of researchers' toughest challenges. Developments in the knowledge discovery process, data models, structures, and design serve as answers and solutions to these emerging challenges.

Data Mining

Author : Bhavani Thuraisingham
Publisher : CRC Press
Page : 288 pages
File Size : 45,8 Mb
Release : 2014-01-23
Category : Computers
ISBN : 9781482252507

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Data Mining by Bhavani Thuraisingham Pdf

Focusing on a data-centric perspective, this book provides a complete overview of data mining: its uses, methods, current technologies, commercial products, and future challenges. Three parts divide Data Mining: Part I describes technologies for data mining - database systems, warehousing, machine learning, visualization, decision support, statistics, parallel processing, and architectural support for data mining Part II presents tools and techniques - getting the data ready, carrying out the mining, pruning the results, evaluating outcomes, defining specific approaches, examining a specific technique based on logic programming, and citing literature and vendors for up-to-date information Part III examines emerging trends - mining distributed and heterogeneous data sources; multimedia data, such as text, images, video; mining data on the World Wide Web; metadata aspects of mining; and privacy issues. This self-contained book also contains two appendices providing exceptional information on technologies, such as data management, and artificial intelligence. Is there a need for mining? Do you have the right tools? Do you have the people to do the work? Do you have sufficient funds allocated to the project? All these answers must be answered before embarking on a project. Data Mining provides singular guidance on appropriate applications for specific techniques as well as thoroughly assesses valuable product information.

Evolving Application Domains of Data Warehousing and Mining: Trends and Solutions

Author : Furtado, Pedro Nuno San-Banto
Publisher : IGI Global
Page : 364 pages
File Size : 44,5 Mb
Release : 2009-09-30
Category : Computers
ISBN : 9781605668178

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Evolving Application Domains of Data Warehousing and Mining: Trends and Solutions by Furtado, Pedro Nuno San-Banto Pdf

"This book provides insight into the latest findings concerning data warehousing, data mining, and their applications in everyday human activities"--Provided by publisher.

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains

Author : Kumar, A.V. Senthil
Publisher : IGI Global
Page : 414 pages
File Size : 41,8 Mb
Release : 2010-08-31
Category : Computers
ISBN : 9781609600693

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Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains by Kumar, A.V. Senthil Pdf

Knowledge Discovery Practices and Emerging Applications of Data Mining: Trends and New Domains introduces the reader to recent research activities in the field of data mining. This book covers association mining, classification, mobile marketing, opinion mining, microarray data mining, internet mining and applications of data mining on biological data, telecommunication and distributed databases, among others, while promoting understanding and implementation of data mining techniques in emerging domains.

Educational Data Mining

Author : Alejandro Peña-Ayala
Publisher : Springer
Page : 468 pages
File Size : 42,7 Mb
Release : 2013-11-08
Category : Technology & Engineering
ISBN : 9783319027388

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Educational Data Mining by Alejandro Peña-Ayala Pdf

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

Author : Anonim
Publisher : BoD – Books on Demand
Page : 226 pages
File Size : 47,6 Mb
Release : 2022-03-30
Category : Computers
ISBN : 9781839692666

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Data Mining by Anonim Pdf

The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics. This book presents basic concepts, ideas, and research in data mining.

Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments

Author : Taniar, David,Rusu, Laura Irina
Publisher : IGI Global
Page : 448 pages
File Size : 48,9 Mb
Release : 2009-12-31
Category : Computers
ISBN : 9781605667188

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Strategic Advancements in Utilizing Data Mining and Warehousing Technologies: New Concepts and Developments by Taniar, David,Rusu, Laura Irina Pdf

"This book presents and disseminates new concepts and developments in the areas of data warehousing and data mining, in particular on the research trends shaped during the last few years"--Provided by publisher.

Introduction to Data Mining and its Applications

Author : S. Sumathi,S.N. Sivanandam
Publisher : Springer
Page : 828 pages
File Size : 43,7 Mb
Release : 2006-10-12
Category : Computers
ISBN : 9783540343516

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Introduction to Data Mining and its Applications by S. Sumathi,S.N. Sivanandam Pdf

This book explores the concepts of data mining and data warehousing, a promising and flourishing frontier in database systems, and presents a broad, yet in-depth overview of the field of data mining. Data mining is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, neural networks, statistics, pattern recognition, knowledge based systems, knowledge acquisition, information retrieval, high performance computing and data visualization.

Data Mining: Concepts, Methodologies, Tools, and Applications

Author : Management Association, Information Resources
Publisher : IGI Global
Page : 2120 pages
File Size : 54,9 Mb
Release : 2012-11-30
Category : Computers
ISBN : 9781466624566

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Data Mining: Concepts, Methodologies, Tools, and Applications by Management Association, Information Resources Pdf

Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.

New Trends in Data Warehousing and Data Analysis

Author : Stanisław Kozielski,Robert Wrembel
Publisher : Springer Science & Business Media
Page : 365 pages
File Size : 53,9 Mb
Release : 2008-11-21
Category : Business & Economics
ISBN : 0387874305

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New Trends in Data Warehousing and Data Analysis by Stanisław Kozielski,Robert Wrembel Pdf

Most of modern enterprises, institutions, and organizations rely on knowledge-based management systems. In these systems, knowledge is gained from data analysis. Today, knowledge-based management systems include data warehouses as their core components. Data integrated in a data warehouse are analyzed by the so-called On-Line Analytical Processing (OLAP) applications designed to discover trends, patterns of behavior, and anomalies as well as finding dependencies between data. Massive amounts of integrated data and the complexity of integrated data coming from many different sources make data integration and processing challenging. New Trends in Data Warehousing and Data Analysis brings together the most recent research and practical achievements in the DW and OLAP technologies. It provides an up-to-date bibliography of published works and the resource of research achievements. Finally, the book assists in the dissemination of knowledge in the field of advanced DW and OLAP.

Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics

Author : Haruna Chiroma,Shafi’i M. Abdulhamid,Philippe Fournier-Viger,Nuno M. Garcia
Publisher : Springer Nature
Page : 316 pages
File Size : 50,7 Mb
Release : 2021-04-01
Category : Technology & Engineering
ISBN : 9783030662882

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Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics by Haruna Chiroma,Shafi’i M. Abdulhamid,Philippe Fournier-Viger,Nuno M. Garcia Pdf

This book addresses theories and empirical procedures for the application of machine learning and data mining to solve problems in cyber dynamics. It explains the fundamentals of cyber dynamics, and presents how these resilient algorithms, strategies, techniques can be used for the development of the cyberspace environment such as: cloud computing services; cyber security; data analytics; and, disruptive technologies like blockchain. The book presents new machine learning and data mining approaches in solving problems in cyber dynamics. Basic concepts, related work reviews, illustrations, empirical results and tables are integrated in each chapter to enable the reader to fully understand the concepts, methodology, and the results presented. The book contains empirical solutions of problems in cyber dynamics ready for industrial applications. The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.

Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques

Author : Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚
Publisher : IGI Global
Page : 852 pages
File Size : 50,7 Mb
Release : 2009-08-31
Category : Computers
ISBN : 9781605667676

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Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques by Olivas, Emilio Soria,Guerrero, Jos‚ David Mart¡n,Martinez-Sober, Marcelino,Magdalena-Benedito, Jose Rafael,Serrano L¢pez, Antonio Jos‚ Pdf

"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.

Data Mining: Concepts and Techniques

Author : Jiawei Han,Micheline Kamber,Jian Pei
Publisher : Elsevier
Page : 740 pages
File Size : 49,6 Mb
Release : 2011-06-09
Category : Computers
ISBN : 9780123814807

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Data Mining: Concepts and Techniques by Jiawei Han,Micheline Kamber,Jian Pei Pdf

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

Social Network Mining, Analysis, and Research Trends

Author : I-Hsien Ting,Tzung-Pei Hong,Leon Shyue-Liang Wang
Publisher : Unknown
Page : 407 pages
File Size : 54,6 Mb
Release : 2012
Category : Data mining
ISBN : 1613505159

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Social Network Mining, Analysis, and Research Trends by I-Hsien Ting,Tzung-Pei Hong,Leon Shyue-Liang Wang Pdf

"This book covers current research trends in the area of social networks analysis and mining, sharing research from experts in the social network analysis and mining communities, as well as practitioners from social science, business, and computer science"--Provided by publisher.

Data Mining

Author : Ciza Thomas
Publisher : Unknown
Page : 190 pages
File Size : 40,5 Mb
Release : 2018
Category : Electronic computers. Computer science
ISBN : 1789235979

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Data Mining by Ciza Thomas Pdf

This book on data mining explores a broad set of ideas and presents some of the state-of-the-art research in this field. The book is triggered by pervasive applications that retrieve knowledge from real-world big data. Data mining finds applications in the entire spectrum of science and technology including basic sciences to life sciences and medicine, to social, economic, and cognitive sciences, to engineering and computers. The chapters discuss various applications and research frontiers in data mining with algorithms and implementation details for use in real-world. This can be through characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, etc. The intended audience of this book will mainly consist of researchers, research students, practitioners, data analysts, and business professionals who seek information on the various data mining techniques and their applications.