Artificial Intelligence in Data Mining Book

Artificial Intelligence in Data Mining


  • Author : D. Binu
  • Publisher : Academic Press
  • Release Date : 2021-02-17
  • Genre: Science
  • Pages : 270
  • ISBN 10 : 9780128206164

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Artificial Intelligence in Data Mining Excerpt :

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

Artificial Intelligence and Data Mining Approaches in Security Frameworks Book

Artificial Intelligence and Data Mining Approaches in Security Frameworks


  • Author : Neeraj Bhargava
  • Publisher : John Wiley & Sons
  • Release Date : 2021-08-24
  • Genre: Technology & Engineering
  • Pages : 322
  • ISBN 10 : 9781119760405

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Artificial Intelligence and Data Mining Approaches in Security Frameworks Excerpt :

ARTIFICIAL INTELLIGENCE AND DATA MINING IN SECURITY FRAMEWORKS Written and edited by a team of experts in the field, this outstanding new volume offers solutions to the problems of security, outlining the concepts behind allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to artificial intelligence. Successful application of security frameworks to enable meaningful, cost effective, personalized security service is a primary aim of engineers and researchers today. However realizing this goal requires effective understanding, application and amalgamation of AI and data mining and several other computing technologies to deploy such a system in an effective manner. This book provides state of the art approaches of artificial intelligence and data mining in these areas. It includes areas of detection, prediction, as well as future framework identification, development, building service systems and analytical aspects. In all these topics, applications of AI and data mining, such as artificial neural networks, fuzzy logic, genetic algorithm and hybrid mechanisms, are explained and explored. This book is aimed at the modeling and performance prediction of efficient security framework systems, bringing to light a new dimension in the theory and practice. This groundbreaking new v

Artificial Intelligence and Data Mining in Healthcare Book

Artificial Intelligence and Data Mining in Healthcare


  • Author : Malek Masmoudi
  • Publisher : Springer Nature
  • Release Date : 2021
  • Genre: Artificial intelligence
  • Pages : 195
  • ISBN 10 : 9783030452407

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Artificial Intelligence and Data Mining in Healthcare Excerpt :

This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.

Machine Learning and Data Mining Book
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Machine Learning and Data Mining


  • Author : Igor Kononenko
  • Publisher : Horwood Publishing
  • Release Date : 2007-04-30
  • Genre: Computers
  • Pages : 484
  • ISBN 10 : 1904275214

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Machine Learning and Data Mining Excerpt :

Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. Written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining, this text is suitable foradvanced undergraduates, postgraduates and tutors in a wide area of computer science and technology, as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to libraries and bookshelves of the many companies who are using the principles of data mining to effectively deliver solid business and industry solutions.

Artificial Intelligence and Data Mining for Mergers and Acquisitions Book

Artificial Intelligence and Data Mining for Mergers and Acquisitions


  • Author : Debasis Chanda
  • Publisher : CRC Press
  • Release Date : 2021-03-18
  • Genre: Business & Economics
  • Pages : 263
  • ISBN 10 : 9780429755408

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Artificial Intelligence and Data Mining for Mergers and Acquisitions Excerpt :

The goal of this book is to present a modeling framework for the Virtual Organization that is focused on process composition. This framework uses Predicate Calculus Knowledge Bases. Petri Net-based modeling is also discussed. In this context, a Data Mining model is proposed, using a fuzzy mathematical approach, aiming to discover knowledge. A Knowledge-Based framework has been proposed in order to present an all-inclusive knowledge store for static and dynamic properties. Toward this direction, a Knowledge Base is created, and inferences are arrived at. This book features an advisory tool for Mergers and Acquisitions of Organizations using the Fuzzy Data Mining Framework and highlights the novelty of a Knowledge-Based Service-Oriented Architecture approach and development of an Enterprise Architectural model using AI that serves a wide audience. Students of Strategic Management in business schools and postgraduate programs in technology institutes seeking application areas of AI and Data Mining, as well as business/technology professionals in organizations aiming to create value through Mergers and Acquisitions and elsewhere, will benefit from the reading of this book.

Machine Learning and Data Mining in Aerospace Technology Book

Machine Learning and Data Mining in Aerospace Technology


  • Author : Aboul Ella Hassanien
  • Publisher : Springer
  • Release Date : 2019-07-02
  • Genre: Technology & Engineering
  • Pages : 232
  • ISBN 10 : 9783030202125

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Machine Learning and Data Mining in Aerospace Technology Excerpt :

This book explores the main concepts, algorithms, and techniques of Machine Learning and data mining for aerospace technology. Satellites are the ‘eagle eyes’ that allow us to view massive areas of the Earth simultaneously, and can gather more data, more quickly, than tools on the ground. Consequently, the development of intelligent health monitoring systems for artificial satellites – which can determine satellites’ current status and predict their failure based on telemetry data – is one of the most important current issues in aerospace engineering. This book is divided into three parts, the first of which discusses central problems in the health monitoring of artificial satellites, including tensor-based anomaly detection for satellite telemetry data and machine learning in satellite monitoring, as well as the design, implementation, and validation of satellite simulators. The second part addresses telemetry data analytics and mining problems, while the last part focuses on security issues in telemetry data.

Introduction to Algorithms for Data Mining and Machine Learning Book

Introduction to Algorithms for Data Mining and Machine Learning


  • Author : Xin-She Yang
  • Publisher : Academic Press
  • Release Date : 2019-06-17
  • Genre: Mathematics
  • Pages : 188
  • ISBN 10 : 9780128172179

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Introduction to Algorithms for Data Mining and Machine Learning Excerpt :

Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data. Presents an informal, theorem-free approach with concise, compact coverage of all fundamental topics Includes worked examples that help users increase confidence in their understanding of key algorithms, thus encouraging self-study Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages

Data Mining and Machine Learning Book

Data Mining and Machine Learning


  • Author : Mohammed J. Zaki
  • Publisher : Cambridge University Press
  • Release Date : 2020-01-30
  • Genre: Business & Economics
  • Pages : 779
  • ISBN 10 : 9781108473989

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Data Mining and Machine Learning Excerpt :

New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

Encyclopedia of Machine Learning Book

Encyclopedia of Machine Learning


  • Author : Claude Sammut
  • Publisher : Springer Science & Business Media
  • Release Date : 2011-03-28
  • Genre: Computers
  • Pages : 1061
  • ISBN 10 : 9780387307688

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Encyclopedia of Machine Learning Excerpt :

This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Machine Learning and Data Mining for Sports Analytics Book

Machine Learning and Data Mining for Sports Analytics


  • Author : Ulf Brefeld
  • Publisher : Springer
  • Release Date : 2019-04-06
  • Genre: Computers
  • Pages : 179
  • ISBN 10 : 9783030172749

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Machine Learning and Data Mining for Sports Analytics Excerpt :

This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018. The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.

Nature Inspired Computation in Data Mining and Machine Learning Book

Nature Inspired Computation in Data Mining and Machine Learning


  • Author : Xin-She Yang
  • Publisher : Springer Nature
  • Release Date : 2019-09-03
  • Genre: Technology & Engineering
  • Pages : 273
  • ISBN 10 : 9783030285531

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Nature Inspired Computation in Data Mining and Machine Learning Excerpt :

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning algorithms over cloud, extreme learning machines, object categorization, particle swarm optimization, flower pollination and firefly algorithms, and neural networks, it also presents case studies and applications, including classifications of crisis-related tweets, extraction of named entities in the Tamil language, performance-based prediction of diseases, and healthcare services. This book is both a valuable a reference resource and a practical guide for students, researchers and professionals in computer science, data and management sciences, artificial intelligence and machine learning.

Data Mining and Machine Learning in Cybersecurity Book

Data Mining and Machine Learning in Cybersecurity


  • Author : Sumeet Dua
  • Publisher : CRC Press
  • Release Date : 2016-04-19
  • Genre: Computers
  • Pages : 256
  • ISBN 10 : 9781439839430

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Data Mining and Machine Learning in Cybersecurity Excerpt :

With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible

Machine Learning and Data Mining for Sports Analytics Book

Machine Learning and Data Mining for Sports Analytics


  • Author : Ulf Brefeld
  • Publisher : Springer Nature
  • Release Date : 2020-12-09
  • Genre: Computers
  • Pages : 141
  • ISBN 10 : 9783030649128

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Machine Learning and Data Mining for Sports Analytics Excerpt :

This book constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. Due to the COVID-19 pandemic the conference was held online. The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.

Machine Learning and Data Mining for Computer Security Book

Machine Learning and Data Mining for Computer Security


  • Author : Marcus A. Maloof
  • Publisher : Springer Science & Business Media
  • Release Date : 2006-02-28
  • Genre: Computers
  • Pages : 210
  • ISBN 10 : 9781846282539

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Machine Learning and Data Mining for Computer Security Excerpt :

"Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This book has a strong focus on information processing and combines and extends results from computer security. The first part of the book surveys the data sources, the learning and mining methods, evaluation methodologies, and past work relevant for computer security. The second part of the book consists of articles written by the top researchers working in this area. These articles deals with topics of host-based intrusion detection through the analysis of audit trails, of command sequences and of system calls as well as network intrusion detection through the analysis of TCP packets and the detection of malicious executables. This book fills the great need for a book that collects and frames work on developing and applying methods from machine learning and data mining to problems in computer security.

Intelligent Data Warehousing Book

Intelligent Data Warehousing


  • Author : Zhengxin Chen
  • Publisher : CRC Press
  • Release Date : 2001-12-13
  • Genre: Computers
  • Pages : 256
  • ISBN 10 : 9781420040616

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Intelligent Data Warehousing Excerpt :

Effective decision support systems (DSS) are quickly becoming key to businesses gaining a competitive advantage, and the effectiveness of these systems depends on the ability to construct, maintain, and extract information from data warehouses. While many still perceive data warehousing as a subdiscipline of management information systems (MIS), in fact many of its advances have and will continue to come from the computer science arena. Intelligent Data Warehousing presents the state of the art in data warehousing research and practice from a perspective that integrates business applications and computer science. It brings the intelligent techniques associated with artificial intelligence (AI) to the entire process of data warehousing, including data preparation, storage, and mining. Part I provides an overview of the main ideas and fundamentals of data mining, artificial intelligence, business intelligence, and data warehousing. Part II presents core materials on data warehousing, and Part III explores data analysis and knowledge discovery in the data warehousing environment, including how to perform intelligent data analysis and the discovery of influential association patterns. Bridging the gap between theoretical research and business applications, this book summarizes the main ideas behind recent research developments rather than setting forth technical details, and it presents case studies that show the how-to's of implementing these ideas. The result is a practical, first-of-its-kind book that brings together scattered research, unites MIS with computer science, and melds intelligent techniques with data warehousing.