Design and Implementation of Data Mining Tools PDF Download

Author: Bhavani Thuraisingham
Publisher: CRC Press
ISBN: 1420045911
Category : Computers
Languages : en
Pages : 272

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Book Description
Focusing on three applications of data mining, Design and Implementation of Data Mining Tools explains how to create and employ systems and tools for intrusion detection, Web page surfing prediction, and image classification. Mainly based on the authors' own research work, the book takes a practical approach to the subject.The first part of the boo

Author:
Publisher:
ISBN:
Category : Data mining
Languages : en
Pages :

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Author: Mehedy Masud
Publisher: CRC Press
ISBN: 1439854556
Category : Computers
Languages : en
Pages : 450

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Book Description
Although the use of data mining for security and malware detection is quickly on the rise, most books on the subject provide high-level theoretical discussions to the near exclusion of the practical aspects. Breaking the mold, Data Mining Tools for Malware Detection provides a step-by-step breakdown of how to develop data mining tools for malware d

Author: Mark F. Hornick
Publisher: Morgan Kaufmann
ISBN: 9780123704528
Category : Computers
Languages : en
Pages : 520

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Book Description
Java Data Mining (JDM) is a standard now implemented in core DBMSs and data mining/analysis software. Ideal for both the beginner and expert, this text is an essential guide to understanding and using the JDM standard interface.

Author: John Macintyre
Publisher: Springer Nature
ISBN: 3030895084
Category : Computers
Languages : en
Pages : 1169

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Book Description
This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Author: Ken Yale
Publisher: Elsevier
ISBN: 0124166458
Category : Mathematics
Languages : en
Pages : 824

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Book Description
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

Author: Alejandro Vaisman
Publisher: Springer Nature
ISBN: 366265167X
Category : Computers
Languages : en
Pages : 696

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Book Description
With this textbook, Vaisman and Zimányi deliver excellent coverage of data warehousing and business intelligence technologies ranging from the most basic principles to recent findings and applications. To this end, their work is structured into three parts. Part I describes “Fundamental Concepts” including conceptual and logical data warehouse design, as well as querying using MDX, DAX and SQL/OLAP. This part also covers data analytics using Power BI and Analysis Services. Part II details “Implementation and Deployment,” including physical design, ETL and data warehouse design methodologies. Part III covers “Advanced Topics” and it is almost completely new in this second edition. This part includes chapters with an in-depth coverage of temporal, spatial, and mobility data warehousing. Graph data warehouses are also covered in detail using Neo4j. The last chapter extensively studies big data management and the usage of Hadoop, Spark, distributed, in-memory, columnar, NoSQL and NewSQL database systems, and data lakes in the context of analytical data processing. As a key characteristic of the book, most of the topics are presented and illustrated using application tools. Specifically, a case study based on the well-known Northwind database illustrates how the concepts presented in the book can be implemented using Microsoft Analysis Services and Power BI. All chapters have been revised and updated to the latest versions of the software tools used. KPIs and Dashboards are now also developed using DAX and Power BI, and the chapter on ETL has been expanded with the implementation of ETL processes in PostgreSQL. Review questions and exercises complement each chapter to support comprehensive student learning. Supplemental material to assist instructors using this book as a course text is available online and includes electronic versions of the figures, solutions to all exercises, and a set of slides accompanying each chapter. Overall, students, practitioners and researchers alike will find this book the most comprehensive reference work on data warehouses, with key topics described in a clear and educational style. “I can only invite you to dive into the contents of the book, feeling certain that once you have completed its reading (or maybe, targeted parts of it), you will join me in expressing our gratitude to Alejandro and Esteban, for providing such a comprehensive textbook for the field of data warehousing in the first place, and for keeping it up to date with the recent developments, in this current second edition.” From the foreword by Panos Vassiliadis, University of Ioannina, Greece.

Author: Christopher Westphal
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 648

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Book Description
Cutting-edge data mining techniques and tools for solving your toughest analytical problems Data Mining Solutions In down-to-earth language, data mining experts Christopher Westphal and Teresa Blaxton introduce a brand new approach to data mining analysis. Through their extensive real-world experience, they have developed and documented many practical and proven techniques to make your own data mining efforts more successful. You'll get a refreshing "out-of-the-box" approach to data mining that will help you maximize your time and problem-solving resources, and prepare for the next wave of data mining-visualization. You will read about ways in which data mining has been used to: * Discover patterns of insider trading in the stock market * Evaluate the utility of marketing campaigns * Analyze retail sales patterns across geographic regions * Identify money laundering operations * Target DNA sequences for pharmaceutical testing and development The book is accompanied by a CD-ROM that contains: * Demo and trial versions of numerous visual data mining tools * Active web-page links for each of the products profiled * GIF files corresponding to all book images

Author: Jiawei Han
Publisher: Elsevier
ISBN: 0123814804
Category : Computers
Languages : en
Pages : 740

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Book Description
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

Author: Subhransu Sekhar Dash
Publisher: Springer
ISBN: 9811031746
Category : Technology & Engineering
Languages : en
Pages : 842

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Book Description
The volume is a collection of high-quality peer-reviewed research papers presented in the International Conference on Artificial Intelligence and Evolutionary Computation in Engineering Systems (ICAIECES 2016) held at SRM University, Chennai, Tamilnadu, India. This conference is an international forum for industry professionals and researchers to deliberate and state their research findings, discuss the latest advancements and explore the future directions in the emerging areas of engineering and technology. The book presents original work and novel ideas, information, techniques and applications in the field of communication, computing and power technologies.