Real World Data Mining Applications

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Real World Data Mining Applications

Mahmoud Abou-Nasr,Stefan Lessmann,Robert Stahlbock,Gary M. Weiss

Author : Mahmoud Abou-Nasr,Stefan Lessmann,Robert Stahlbock,Gary M. Weiss
Publisher : Springer
Page : 418 pages
File Size : 41,6 Mb
Release : 2014-11-13
Category : Business & Economics
ISBN : 9783319078120

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Real World Data Mining Applications by Mahmoud Abou-Nasr,Stefan Lessmann,Robert Stahlbock,Gary M. Weiss Pdf

Data mining applications range from commercial to social domains, with novel applications appearing swiftly; for example, within the context of social networks. The expanding application sphere and social reach of advanced data mining raise pertinent issues of privacy and security. Present-day data mining is a progressive multidisciplinary endeavor. This inter- and multidisciplinary approach is well reflected within the field of information systems. The information systems research addresses software and hardware requirements for supporting computationally and data-intensive applications. Furthermore, it encompasses analyzing system and data aspects, and all manual or automated activities. In that respect, research at the interface of information systems and data mining has significant potential to produce actionable knowledge vital for corporate decision-making. The aim of the proposed volume is to provide a balanced treatment of the latest advances and developments in data mining; in particular, exploring synergies at the intersection with information systems. It will serve as a platform for academics and practitioners to highlight their recent achievements and reveal potential opportunities in the field. Thanks to its multidisciplinary nature, the volume is expected to become a vital resource for a broad readership ranging from students, throughout engineers and developers, to researchers and academics.

Data Mining Applications with R

Yanchang Zhao,Yonghua Cen

Author : Yanchang Zhao,Yonghua Cen
Publisher : Academic Press
Page : 514 pages
File Size : 40,7 Mb
Release : 2013-11-26
Category : Computers
ISBN : 9780124115200

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Data Mining Applications with R by Yanchang Zhao,Yonghua Cen Pdf

Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries Presents various case studies in real-world applications, which will help readers to apply the techniques in their work Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves

Real-World Data Mining

Dursun Delen

Author : Dursun Delen
Publisher : FT Press
Page : 289 pages
File Size : 54,9 Mb
Release : 2014-12-16
Category : Business & Economics
ISBN : 9780133551112

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Real-World Data Mining by Dursun Delen Pdf

Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials. Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based.

Handbook of Statistical Analysis and Data Mining Applications

Robert Nisbet,Gary Miner,Ken Yale

Author : Robert Nisbet,Gary Miner,Ken Yale
Publisher : Elsevier
Page : 822 pages
File Size : 53,7 Mb
Release : 2017-11-09
Category : Mathematics
ISBN : 9780124166455

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Handbook of Statistical Analysis and Data Mining Applications by Robert Nisbet,Gary Miner,Ken Yale Pdf

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Practical Data Mining Techniques and Applications

Ketan Shah,Neepa Shah,Vinaya Sawant,Neeraj Parolia

Author : Ketan Shah,Neepa Shah,Vinaya Sawant,Neeraj Parolia
Publisher : Unknown
Page : 0 pages
File Size : 40,7 Mb
Release : 2023
Category : Data mining
ISBN : 1003390226

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Practical Data Mining Techniques and Applications by Ketan Shah,Neepa Shah,Vinaya Sawant,Neeraj Parolia Pdf

Data mining techniques and algorithms are extensively used to build real-world applications. A practical approach can be applied to data mining techniques to build applications. Once deployed, an application enables the developers to work on the users' goals and mold the algorithms with respect to users' perspectives. Practical Data Mining Techniques and Applications focuses on various concepts related to data mining and how these techniques can be used to develop and deploy applications. The book provides a systematic composition of fundamental concepts of data mining blended with practical applications. The aim of this book is to provide access to practical data mining applications and techniques to help readers gain an understanding of data mining in practice. Readers also learn how relevant techniques and algorithms are applied to solve problems and to provide solutions to real-world applications in different domains. This book can help academicians to extend their knowledge of the field as well as their understanding of applications based on different techniques to gain greater insight. It can also help researchers with real-world applications by diving deeper into the domain. Computing science students, application developers, and business professionals may also benefit from this examination of applied data science techniques. By highlighting an overall picture of the field, introducing various mining techniques, and focusing on different applications and research directions using these methods, this book can motivate discussions among academics, researchers, professionals, and students to exchange and develop their views regarding the dynamic field that is data mining.

Building Data Mining Applications for CRM

Alex Berson,Stephen Smith,Kurt Thearling

Author : Alex Berson,Stephen Smith,Kurt Thearling
Publisher : McGraw-Hill Companies
Page : 548 pages
File Size : 54,8 Mb
Release : 2000
Category : Computers
ISBN : UVA:X004393307

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Building Data Mining Applications for CRM by Alex Berson,Stephen Smith,Kurt Thearling Pdf

Learn how to use customer relationship management (CRM) techniques to give your company an edge in the competitive marketplace. --

Mobile Data Mining and Applications

Hao Jiang,Qimei Chen,Yuanyuan Zeng,Deshi Li

Author : Hao Jiang,Qimei Chen,Yuanyuan Zeng,Deshi Li
Publisher : Springer
Page : 227 pages
File Size : 47,8 Mb
Release : 2019-05-10
Category : Technology & Engineering
ISBN : 9783030165031

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Mobile Data Mining and Applications by Hao Jiang,Qimei Chen,Yuanyuan Zeng,Deshi Li Pdf

This book focuses on mobile data and its applications in the wireless networks of the future. Several topics form the basis of discussion, from a mobile data mining platform for collecting mobile data, to mobile data processing, and mobile feature discovery. Usage of mobile data mining is addressed in the context of three applications: wireless communication optimization, applications of mobile data mining on the cellular networks of the future, and how mobile data shapes future cities. In the discussion of wireless communication optimization, both licensed and unlicensed spectra are exploited. Advanced topics include mobile offloading, resource sharing, user association, network selection and network coexistence. Mathematical tools, such as traditional convexappl/non-convex, stochastic processing and game theory are used to find objective solutions. Discussion of the applications of mobile data mining to cellular networks of the future includes topics such as green communication networks, 5G networks, and studies of the problems of cell zooming, power control, sleep/wake, and energy saving. The discussion of mobile data mining in the context of smart cities of the future covers applications in urban planning and environmental monitoring: the technologies of deep learning, neural networks, complex networks, and network embedded data mining. Mobile Data Mining and Applications will be of interest to wireless operators, companies, governments as well as interested end users.

Data Mining and Knowledge Discovery in Real Life Applications

Julio Ponce,Adem Karahoca

Author : Julio Ponce,Adem Karahoca
Publisher : BoD – Books on Demand
Page : 404 pages
File Size : 47,5 Mb
Release : 2009-01-01
Category : Computers
ISBN : 9783902613530

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Data Mining and Knowledge Discovery in Real Life Applications by Julio Ponce,Adem Karahoca Pdf

This book presents four different ways of theoretical and practical advances and applications of data mining in different promising areas like Industrialist, Biological, and Social. Twenty six chapters cover different special topics with proposed novel ideas. Each chapter gives an overview of the subjects and some of the chapters have cases with offered data mining solutions. We hope that this book will be a useful aid in showing a right way for the students, researchers and practitioners in their studies.

Applications of Data Mining in E-Business and Finance

C. Soares,Y. Peng,J. Meng

Author : C. Soares,Y. Peng,J. Meng
Publisher : IOS Press
Page : 156 pages
File Size : 46,5 Mb
Release : 2008-08-07
Category : Business & Economics
ISBN : 9781607503545

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Applications of Data Mining in E-Business and Finance by C. Soares,Y. Peng,J. Meng Pdf

The application of Data Mining (DM) technologies has shown an explosive growth in an increasing number of different areas of business, government and science. Two of the most important business areas are finance, in particular in banks and insurance companies, and e-business, such as web portals, e-commerce and ad management services. In spite of the close relationship between research and practice in Data Mining, it is not easy to find information on some of the most important issues involved in real world application of DM technology, from business and data understanding to evaluation and deployment. Papers often describe research that was developed without taking into account constraints imposed by the motivating application. When these issues are taken into account, they are frequently not discussed in detail because the paper must focus on the method. Therefore knowledge that could be useful for those who would like to apply the same approach on a related problem is not shared. The papers in this book address some of these issues. This book is of interest not only to Data Mining researchers and practitioners, but also to students who wish to have an idea of the practical issues involved in Data Mining.

Developing Multi-Database Mining Applications

Animesh Adhikari,Pralhad Ramachandrarao,Witold Pedrycz

Author : Animesh Adhikari,Pralhad Ramachandrarao,Witold Pedrycz
Publisher : Springer Science & Business Media
Page : 134 pages
File Size : 53,9 Mb
Release : 2010-06-14
Category : Computers
ISBN : 9781849960441

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Developing Multi-Database Mining Applications by Animesh Adhikari,Pralhad Ramachandrarao,Witold Pedrycz Pdf

Multi-database mining has been recognized recently as an important and strategically essential area of research in data mining. In this book, we discuss various issues regarding the systematic and efficient development of multi-database mining applications. It explains how systematically one could prepare data warehouses at different branches. As appropriate multi-database mining technique is essential to develop better applications. Also, the efficiency of a multi-database mining application could be improved by processing more patterns in the application. A faster algorithm could also play an important role in developing a better application. Thus the efficiency of a multi-database mining application could be enhanced by choosing an appropriate multi-database mining model, an appropriate pattern synthesizing technique, a better pattern representation technique, and an efficient algorithm for solving the problem. This book illustrates each of these issues either in the context of a specific problem, or in general.

Data Mining for Geoinformatics

Guido Cervone,Jessica Lin,Nigel Waters

Author : Guido Cervone,Jessica Lin,Nigel Waters
Publisher : Springer Science & Business Media
Page : 166 pages
File Size : 55,5 Mb
Release : 2013-08-16
Category : Computers
ISBN : 9781461476696

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Data Mining for Geoinformatics by Guido Cervone,Jessica Lin,Nigel Waters Pdf

The rate at which geospatial data is being generated exceeds our computational capabilities to extract patterns for the understanding of a dynamically changing world. Geoinformatics and data mining focuses on the development and implementation of computational algorithms to solve these problems. This unique volume contains a collection of chapters on state-of-the-art data mining techniques applied to geoinformatic problems of high complexity and important societal value. Data Mining for Geoinformatics addresses current concerns and developments relating to spatio-temporal data mining issues in remotely-sensed data, problems in meteorological data such as tornado formation, estimation of radiation from the Fukushima nuclear power plant, simulations of traffic data using OpenStreetMap, real time traffic applications of data stream mining, visual analytics of traffic and weather data and the exploratory visualization of collective, mobile objects such as the flocking behavior of wild chickens. This book is designed for researchers and advanced-level students focused on computer science, earth science and geography as a reference or secondary text book. Practitioners working in the areas of data mining and geoscience will also find this book to be a valuable reference.

Innovative Applications in Data Mining

Nadia Nedjah,Luiza de Macedo Mourelle,Janusz Kacprzyk

Author : Nadia Nedjah,Luiza de Macedo Mourelle,Janusz Kacprzyk
Publisher : Springer Science & Business Media
Page : 132 pages
File Size : 46,7 Mb
Release : 2009-01-17
Category : Mathematics
ISBN : 9783540880448

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Innovative Applications in Data Mining by Nadia Nedjah,Luiza de Macedo Mourelle,Janusz Kacprzyk Pdf

Data mining consists of attempting to discover novel and useful knowledge from data, trying to find patterns among datasets that can help in intelligent decision making. However, reports of real-world case studies are not generally detailed in the literature, due to the fact that they are usually based on proprietary datasets, making it impossible to publish the results. This kind of situation makes hard to evaluate, in a precise way, the degree of effectiveness of data mining techniques in real-world applications. On the other hand, researchers of this field of expertise usually exploit public-domain datasets. This volume offers a wide spectrum of research work developed for data mining for real-world application. In the following, we give a brief introduction of the chapters that are included in this book.

Data Mining for Business Applications

Longbing Cao,Philip S. Yu,Chengqi Zhang,Huaifeng Zhang

Author : Longbing Cao,Philip S. Yu,Chengqi Zhang,Huaifeng Zhang
Publisher : Springer Science & Business Media
Page : 310 pages
File Size : 40,7 Mb
Release : 2008-10-03
Category : Computers
ISBN : 9780387794204

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Data Mining for Business Applications by Longbing Cao,Philip S. Yu,Chengqi Zhang,Huaifeng Zhang Pdf

Data Mining for Business Applications presents the state-of-the-art research and development outcomes on methodologies, techniques, approaches and successful applications in the area. The contributions mark a paradigm shift from “data-centered pattern mining” to “domain driven actionable knowledge discovery” for next-generation KDD research and applications. The contents identify how KDD techniques can better contribute to critical domain problems in theory and practice, and strengthen business intelligence in complex enterprise applications. The volume also explores challenges and directions for future research and development in the dialogue between academia and business.

R and Data Mining

Yanchang Zhao

Author : Yanchang Zhao
Publisher : Academic Press
Page : 256 pages
File Size : 51,8 Mb
Release : 2012-12-31
Category : Mathematics
ISBN : 9780123972712

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R and Data Mining by Yanchang Zhao Pdf

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for statistical computing and graphics. The book provides practical methods for using R in applications from academia to industry to extract knowledge from vast amounts of data. Readers will find this book a valuable guide to the use of R in tasks such as classification and prediction, clustering, outlier detection, association rules, sequence analysis, text mining, social network analysis, sentiment analysis, and more. Data mining techniques are growing in popularity in a broad range of areas, from banking to insurance, retail, telecom, medicine, research, and government. This book focuses on the modeling phase of the data mining process, also addressing data exploration and model evaluation. With three in-depth case studies, a quick reference guide, bibliography, and links to a wealth of online resources, R and Data Mining is a valuable, practical guide to a powerful method of analysis. Presents an introduction into using R for data mining applications, covering most popular data mining techniques Provides code examples and data so that readers can easily learn the techniques Features case studies in real-world applications to help readers apply the techniques in their work

Artificial Intelligence in Data Mining

D. Binu,B.R. Rajakumar

Author : D. Binu,B.R. Rajakumar
Publisher : Academic Press
Page : 270 pages
File Size : 48,5 Mb
Release : 2021-02-17
Category : Science
ISBN : 9780128206164

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Artificial Intelligence in Data Mining by D. Binu,B.R. Rajakumar Pdf

Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense

Real World Data Mining Applications

Real World Data Mining Applications by Mahmoud Abou-Nasr,Stefan Lessmann,Robert Stahlbock,Gary M. Weiss Pdf

Data Mining Applications with R by Yanchang Zhao,Yonghua Cen Pdf

Real-World Data Mining by Dursun Delen Pdf

Handbook of Statistical Analysis and Data Mining Applications by Robert Nisbet,Gary Miner,Ken Yale Pdf

Practical Data Mining Techniques and Applications by Ketan Shah,Neepa Shah,Vinaya Sawant,Neeraj Parolia Pdf

Building Data Mining Applications for CRM by Alex Berson,Stephen Smith,Kurt Thearling Pdf

Mobile Data Mining and Applications by Hao Jiang,Qimei Chen,Yuanyuan Zeng,Deshi Li Pdf

Data Mining and Knowledge Discovery in Real Life Applications by Julio Ponce,Adem Karahoca Pdf

Applications of Data Mining in E-Business and Finance by C. Soares,Y. Peng,J. Meng Pdf

Developing Multi-Database Mining Applications by Animesh Adhikari,Pralhad Ramachandrarao,Witold Pedrycz Pdf

Data Mining for Geoinformatics by Guido Cervone,Jessica Lin,Nigel Waters Pdf

Innovative Applications in Data Mining by Nadia Nedjah,Luiza de Macedo Mourelle,Janusz Kacprzyk Pdf

Data Mining for Business Applications by Longbing Cao,Philip S. Yu,Chengqi Zhang,Huaifeng Zhang Pdf

R and Data Mining by Yanchang Zhao Pdf

Artificial Intelligence in Data Mining by D. Binu,B.R. Rajakumar Pdf

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