Mastering Data Mining Ms With Data Mining Set

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MASTERING DATA MINING: THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT

Author : Michael J. A. Berry
Publisher :
ISBN 13 : 9788126518258
Total Pages : 512 pages
Book Rating : 4.5/5 (182 download)

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Book Synopsis MASTERING DATA MINING: THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT by : Michael J. A. Berry

Download or read book MASTERING DATA MINING: THE ART AND SCIENCE OF CUSTOMER RELATIONSHIP MANAGEMENT written by Michael J. A. Berry and published by . This book was released on 2008-09-01 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: Special Features: · Best-in-class data mining techniques for solving critical problems in all areas of business· Explains how to pick the right data mining techniques for specific problems· Shows how to perform analysis and evaluate results· Features real-world examples from across various industry sectors· Companion Web site with updates on data mining products and service providers About The Book: Companies have invested in building data warehouses to capture vast amounts of customer information. The payoff comes with mining or getting access to the data within this information gold mine to make better business decisions. Readers and reviewers loved Berry and Linoff's first book, Data Mining Techniques, because the authors so clearly illustrate practical techniques with real benefits for improved marketing and sales. Mastering Data Mining takes off from there-assuming readers know the basic techniques covered in the first book, the authors focus on how to best apply these techniques to real business cases. They start with simple applications and work up to the most powerful and sophisticated examples over the course of about 20 cases. (Ralph Kimball used this same approach in his highly successful Data Warehouse Toolkit). As with their first book, Mastering Data Mining is sufficiently technical for database analysts, but is accessible to technically savvy business and marketing managers. It should also appeal to a new breed of database marketing managers.

Data Mining: Concepts and Techniques

Author : Jiawei Han
Publisher : Elsevier
ISBN 13 : 0123814804
Total Pages : 740 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Data Mining: Concepts and Techniques by : Jiawei Han

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

Data Mining For Dummies

Author : Meta S. Brown
Publisher : John Wiley & Sons
ISBN 13 : 1118893166
Total Pages : 422 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Data Mining For Dummies by : Meta S. Brown

Download or read book Data Mining For Dummies written by Meta S. Brown and published by John Wiley & Sons. This book was released on 2014-09-04 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum. The ability to detect unseen patterns hidden in the numbers exhaustively generated by day-to-day operations allows savvy decision-makers to exploit every tool at their disposal in the pursuit of better business. By creating models and testing whether patterns hold up, it is possible to discover new intelligence that could change your business's entire paradigm for a more successful outcome. Data Mining for Dummies shows you why it doesn't take a data scientist to gain this advantage, and empowers average business people to start shaping a process relevant to their business's needs. In this book, you'll learn the hows and whys of mining to the depths of your data, and how to make the case for heavier investment into data mining capabilities. The book explains the details of the knowledge discovery process including: Model creation, validity testing, and interpretation Effective communication of findings Available tools, both paid and open-source Data selection, transformation, and evaluation Data Mining for Dummies takes you step-by-step through a real-world data-mining project using open-source tools that allow you to get immediate hands-on experience working with large amounts of data. You'll gain the confidence you need to start making data mining practices a routine part of your successful business. If you're serious about doing everything you can to push your company to the top, Data Mining for Dummies is your ticket to effective data mining.

Mastering Data Mining

Author : Cybellium Ltd
Publisher : Cybellium Ltd
ISBN 13 :
Total Pages : 206 pages
Book Rating : 4.8/5 (626 download)

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Book Synopsis Mastering Data Mining by : Cybellium Ltd

Download or read book Mastering Data Mining written by Cybellium Ltd and published by Cybellium Ltd. This book was released on with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncover Hidden Insights and Patterns in Your Data Are you ready to delve into the fascinating realm of data mining? "Mastering Data Mining" is your ultimate guide to unlocking the potential of extracting hidden insights and patterns from your data. Whether you're a data scientist aiming to uncover valuable information or a business professional seeking to make informed decisions, this book equips you with the knowledge and techniques to master the art of data mining. Key Features: 1. Journey into Data Mining: Immerse yourself in the world of data mining, understanding its significance, methodologies, and applications. Build a solid foundation that empowers you to extract meaningful insights from complex datasets. 2. Data Exploration and Preparation: Master the art of data exploration and preparation. Learn how to clean, transform, and preprocess data for effective mining. 3. Exploratory Data Analysis: Delve into exploratory data analysis techniques. Explore visualization, statistical summaries, and data profiling to gain a deeper understanding of your dataset. 4. Supervised Learning Techniques: Uncover the power of supervised learning techniques. Learn how to build predictive models for classification and regression tasks, enabling you to make accurate predictions. 5. Unsupervised Learning and Clustering: Discover unsupervised learning and clustering methods. Explore techniques for grouping similar data points and identifying hidden patterns without predefined labels. 6. Association Rule Mining: Master association rule mining for uncovering relationships in data. Learn how to identify frequent itemsets and extract valuable associations. 7. Text and Web Mining: Explore text and web mining techniques. Learn how to extract insights from textual data and discover patterns in web-based information. 8. Time Series Mining: Delve into time series mining for analyzing sequential data. Learn how to forecast trends, identify anomalies, and make predictions based on temporal patterns. 9. Data Mining Tools and Algorithms: Uncover a range of data mining tools and algorithms. Explore classic algorithms and modern techniques for various data mining tasks. 10. Real-World Applications: Gain insights into real-world use cases of data mining across industries. From customer segmentation to fraud detection, explore how organizations leverage data mining for strategic advantage. Who This Book Is For: "Mastering Data Mining" is an indispensable resource for data scientists, analysts, and business professionals who want to excel in uncovering insights from data. Whether you're new to data mining or seeking advanced techniques, this book will guide you through the intricacies and empower you to harness the full potential of data mining. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Data Mining Techniques

Author : Michael J. A. Berry
Publisher : John Wiley & Sons
ISBN 13 : 0471470643
Total Pages : 671 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Data Mining Techniques by : Michael J. A. Berry

Download or read book Data Mining Techniques written by Michael J. A. Berry and published by John Wiley & Sons. This book was released on 2004-04-09 with total page 671 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Mastering Social Media Mining with Python

Author : Marco Bonzanini
Publisher : Packt Publishing Ltd
ISBN 13 : 1783552026
Total Pages : 333 pages
Book Rating : 4.7/5 (835 download)

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Book Synopsis Mastering Social Media Mining with Python by : Marco Bonzanini

Download or read book Mastering Social Media Mining with Python written by Marco Bonzanini and published by Packt Publishing Ltd. This book was released on 2016-07-29 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: Acquire and analyze data from all corners of the social web with Python About This Book Make sense of highly unstructured social media data with the help of the insightful use cases provided in this guide Use this easy-to-follow, step-by-step guide to apply analytics to complicated and messy social data This is your one-stop solution to fetching, storing, analyzing, and visualizing social media data Who This Book Is For This book is for intermediate Python developers who want to engage with the use of public APIs to collect data from social media platforms and perform statistical analysis in order to produce useful insights from data. The book assumes a basic understanding of the Python Standard Library and provides practical examples to guide you toward the creation of your data analysis project based on social data. What You Will Learn Interact with a social media platform via their public API with Python Store social data in a convenient format for data analysis Slice and dice social data using Python tools for data science Apply text analytics techniques to understand what people are talking about on social media Apply advanced statistical and analytical techniques to produce useful insights from data Build beautiful visualizations with web technologies to explore data and present data products In Detail Your social media is filled with a wealth of hidden data – unlock it with the power of Python. Transform your understanding of your clients and customers when you use Python to solve the problems of understanding consumer behavior and turning raw data into actionable customer insights. This book will help you acquire and analyze data from leading social media sites. It will show you how to employ scientific Python tools to mine popular social websites such as Facebook, Twitter, Quora, and more. Explore the Python libraries used for social media mining, and get the tips, tricks, and insider insight you need to make the most of them. Discover how to develop data mining tools that use a social media API, and how to create your own data analysis projects using Python for clear insight from your social data. Style and approach This practical, hands-on guide will help you learn everything you need to perform data mining for social media. Throughout the book, we take an example-oriented approach to use Python for data analysis and provide useful tips and tricks that you can use in day-to-day tasks.

Mining of Massive Datasets

Author : Jure Leskovec
Publisher : Cambridge University Press
ISBN 13 : 1107077230
Total Pages : 480 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Mining of Massive Datasets by : Jure Leskovec

Download or read book Mining of Massive Datasets written by Jure Leskovec and published by Cambridge University Press. This book was released on 2014-11-13 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in its second edition, this book focuses on practical algorithms for mining data from even the largest datasets.

Introduction to Data Mining and Analytics

Author : Kris Jamsa
Publisher : Jones & Bartlett Learning
ISBN 13 : 1284210480
Total Pages : 687 pages
Book Rating : 4.2/5 (842 download)

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Book Synopsis Introduction to Data Mining and Analytics by : Kris Jamsa

Download or read book Introduction to Data Mining and Analytics written by Kris Jamsa and published by Jones & Bartlett Learning. This book was released on 2020-02-03 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining and Analytics provides a broad and interactive overview of a rapidly growing field. The exponentially increasing rate at which data is generated creates a corresponding need for professionals who can effectively handle its storage, analysis, and translation.

Data Preparation for Data Mining

Author : Dorian Pyle
Publisher : Morgan Kaufmann
ISBN 13 : 9781558605299
Total Pages : 566 pages
Book Rating : 4.6/5 (52 download)

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Book Synopsis Data Preparation for Data Mining by : Dorian Pyle

Download or read book Data Preparation for Data Mining written by Dorian Pyle and published by Morgan Kaufmann. This book was released on 1999-03-22 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the importance of clean, well-structured data as the first step to successful data mining. It shows how data should be prepared prior to mining in order to maximize mining performance.

Mastering Data Mining with Python – Find patterns hidden in your data

Author : Megan Squire
Publisher : Packt Publishing Ltd
ISBN 13 : 178588591X
Total Pages : 269 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Mastering Data Mining with Python – Find patterns hidden in your data by : Megan Squire

Download or read book Mastering Data Mining with Python – Find patterns hidden in your data written by Megan Squire and published by Packt Publishing Ltd. This book was released on 2016-08-29 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to create more powerful data mining applications with this comprehensive Python guide to advance data analytics techniques About This Book Dive deeper into data mining with Python – don't be complacent, sharpen your skills! From the most common elements of data mining to cutting-edge techniques, we've got you covered for any data-related challenge Become a more fluent and confident Python data-analyst, in full control of its extensive range of libraries Who This Book Is For This book is for data scientists who are already familiar with some basic data mining techniques such as SQL and machine learning, and who are comfortable with Python. If you are ready to learn some more advanced techniques in data mining in order to become a data mining expert, this is the book for you! What You Will Learn Explore techniques for finding frequent itemsets and association rules in large data sets Learn identification methods for entity matches across many different types of data Identify the basics of network mining and how to apply it to real-world data sets Discover methods for detecting the sentiment of text and for locating named entities in text Observe multiple techniques for automatically extracting summaries and generating topic models for text See how to use data mining to fix data anomalies and how to use machine learning to identify outliers in a data set In Detail Data mining is an integral part of the data science pipeline. It is the foundation of any successful data-driven strategy – without it, you'll never be able to uncover truly transformative insights. Since data is vital to just about every modern organization, it is worth taking the next step to unlock even greater value and more meaningful understanding. If you already know the fundamentals of data mining with Python, you are now ready to experiment with more interesting, advanced data analytics techniques using Python's easy-to-use interface and extensive range of libraries. In this book, you'll go deeper into many often overlooked areas of data mining, including association rule mining, entity matching, network mining, sentiment analysis, named entity recognition, text summarization, topic modeling, and anomaly detection. For each data mining technique, we'll review the state-of-the-art and current best practices before comparing a wide variety of strategies for solving each problem. We will then implement example solutions using real-world data from the domain of software engineering, and we will spend time learning how to understand and interpret the results we get. By the end of this book, you will have solid experience implementing some of the most interesting and relevant data mining techniques available today, and you will have achieved a greater fluency in the important field of Python data analytics. Style and approach This book will teach you the intricacies in applying data mining using real-world scenarios and will act as a very practical solution to your data mining needs.

Data Mining with R

Author : Luis Torgo
Publisher : CRC Press
ISBN 13 : 1315399091
Total Pages : 426 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Data Mining with R by : Luis Torgo

Download or read book Data Mining with R written by Luis Torgo and published by CRC Press. This book was released on 2016-11-30 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, including a new chapter that provides an introduction to data mining, to complement the already existing introduction to R. The second part includes case studies, and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies, and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book’s web site. These files include all the code used in the case studies, and they facilitate the "do-it-yourself" approach followed in the book. Designed for users of data analysis tools, as well as researchers and developers, the book should be useful for anyone interested in entering the "world" of R and data mining. About the Author Luís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business’ MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA.

Discovering Knowledge in Data

Author : Daniel T. Larose
Publisher : John Wiley & Sons
ISBN 13 : 0471687537
Total Pages : 240 pages
Book Rating : 4.4/5 (716 download)

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Book Synopsis Discovering Knowledge in Data by : Daniel T. Larose

Download or read book Discovering Knowledge in Data written by Daniel T. Larose and published by John Wiley & Sons. This book was released on 2005-01-28 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn Data Mining by doing data mining Data mining can be revolutionary-but only when it's done right. The powerful black box data mining software now available can produce disastrously misleading results unless applied by a skilled and knowledgeable analyst. Discovering Knowledge in Data: An Introduction to Data Mining provides both the practical experience and the theoretical insight needed to reveal valuable information hidden in large data sets. Employing a "white box" methodology and with real-world case studies, this step-by-step guide walks readers through the various algorithms and statistical structures that underlie the software and presents examples of their operation on actual large data sets. Principal topics include: * Data preprocessing and classification * Exploratory analysis * Decision trees * Neural and Kohonen networks * Hierarchical and k-means clustering * Association rules * Model evaluation techniques Complete with scores of screenshots and diagrams to encourage graphical learning, Discovering Knowledge in Data: An Introduction to Data Mining gives students in Business, Computer Science, and Statistics as well as professionals in the field the power to turn any data warehouse into actionable knowledge. An Instructor's Manual presenting detailed solutions to all the problems in the book is available online.

Data Mining and Data Warehousing

Author : Parteek Bhatia
Publisher : Cambridge University Press
ISBN 13 : 110858585X
Total Pages : 514 pages
Book Rating : 4.1/5 (85 download)

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Book Synopsis Data Mining and Data Warehousing by : Parteek Bhatia

Download or read book Data Mining and Data Warehousing written by Parteek Bhatia and published by Cambridge University Press. This book was released on 2019-06-27 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in lucid language, this valuable textbook brings together fundamental concepts of data mining and data warehousing in a single volume. Important topics including information theory, decision tree, Naïve Bayes classifier, distance metrics, partitioning clustering, associate mining, data marts and operational data store are discussed comprehensively. The textbook is written to cater to the needs of undergraduate students of computer science, engineering and information technology for a course on data mining and data warehousing. The text simplifies the understanding of the concepts through exercises and practical examples. Chapters such as classification, associate mining and cluster analysis are discussed in detail with their practical implementation using Weka and R language data mining tools. Advanced topics including big data analytics, relational data models and NoSQL are discussed in detail. Pedagogical features including unsolved problems and multiple-choice questions are interspersed throughout the book for better understanding.

Principles of Data Mining

Author : David J. Hand
Publisher : MIT Press
ISBN 13 : 9780262082907
Total Pages : 594 pages
Book Rating : 4.0/5 (829 download)

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Book Synopsis Principles of Data Mining by : David J. Hand

Download or read book Principles of Data Mining written by David J. Hand and published by MIT Press. This book was released on 2001-08-17 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.

Data Mining and Decision Support

Author : Dunja Mladenic
Publisher : Springer Science & Business Media
ISBN 13 : 1461502861
Total Pages : 284 pages
Book Rating : 4.4/5 (615 download)

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Book Synopsis Data Mining and Decision Support by : Dunja Mladenic

Download or read book Data Mining and Decision Support written by Dunja Mladenic and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining deals with finding patterns in data that are by user-definition, interesting and valid. It is an interdisciplinary area involving databases, machine learning, pattern recognition, statistics, visualization and others. Decision support focuses on developing systems to help decision-makers solve problems. Decision support provides a selection of data analysis, simulation, visualization and modeling techniques, and software tools such as decision support systems, group decision support and mediation systems, expert systems, databases and data warehouses. Independently, data mining and decision support are well-developed research areas, but until now there has been no systematic attempt to integrate them. Data Mining and Decision Support: Integration and Collaboration, written by leading researchers in the field, presents a conceptual framework, plus the methods and tools for integrating the two disciplines and for applying this technology to business problems in a collaborative setting.

Mastering Java for Data Science

Author : Alexey Grigorev
Publisher : Packt Publishing Ltd
ISBN 13 : 1785887394
Total Pages : 355 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Mastering Java for Data Science by : Alexey Grigorev

Download or read book Mastering Java for Data Science written by Alexey Grigorev and published by Packt Publishing Ltd. This book was released on 2017-04-27 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Java to create a diverse range of Data Science applications and bring Data Science into production About This Book An overview of modern Data Science and Machine Learning libraries available in Java Coverage of a broad set of topics, going from the basics of Machine Learning to Deep Learning and Big Data frameworks. Easy-to-follow illustrations and the running example of building a search engine. Who This Book Is For This book is intended for software engineers who are comfortable with developing Java applications and are familiar with the basic concepts of data science. Additionally, it will also be useful for data scientists who do not yet know Java but want or need to learn it. If you are willing to build efficient data science applications and bring them in the enterprise environment without changing the existing stack, this book is for you! What You Will Learn Get a solid understanding of the data processing toolbox available in Java Explore the data science ecosystem available in Java Find out how to approach different machine learning problems with Java Process unstructured information such as natural language text or images Create your own search engine Get state-of-the-art performance with XGBoost Learn how to build deep neural networks with DeepLearning4j Build applications that scale and process large amounts of data Deploy data science models to production and evaluate their performance In Detail Java is the most popular programming language, according to the TIOBE index, and it is a typical choice for running production systems in many companies, both in the startup world and among large enterprises. Not surprisingly, it is also a common choice for creating data science applications: it is fast and has a great set of data processing tools, both built-in and external. What is more, choosing Java for data science allows you to easily integrate solutions with existing software, and bring data science into production with less effort. This book will teach you how to create data science applications with Java. First, we will revise the most important things when starting a data science application, and then brush up the basics of Java and machine learning before diving into more advanced topics. We start by going over the existing libraries for data processing and libraries with machine learning algorithms. After that, we cover topics such as classification and regression, dimensionality reduction and clustering, information retrieval and natural language processing, and deep learning and big data. Finally, we finish the book by talking about the ways to deploy the model and evaluate it in production settings. Style and approach This is a practical guide where all the important concepts such as classification, regression, and dimensionality reduction are explained with the help of examples.

Always-On Enterprise Information Systems for Business Continuance: Technologies for Reliable and Scalable Operations

Author : Bajgoric, Nijaz
Publisher : IGI Global
ISBN 13 : 1605667242
Total Pages : 344 pages
Book Rating : 4.6/5 (56 download)

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Book Synopsis Always-On Enterprise Information Systems for Business Continuance: Technologies for Reliable and Scalable Operations by : Bajgoric, Nijaz

Download or read book Always-On Enterprise Information Systems for Business Continuance: Technologies for Reliable and Scalable Operations written by Bajgoric, Nijaz and published by IGI Global. This book was released on 2009-08-31 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides chapters describing in more detail the structure of information systems pertaining to enabling technologies, aspects of their implementations, IT/IS governing, risk management, disaster management, interrelated manufacturing and supply chain strategies, and new IT paradigms"--Provided by publisher.