Adaptive Stream Mining Pattern Learning And Mining From Evolving Data Streams


Adaptive Stream Mining Pattern Learning And Mining From Evolving Data Streams
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Adaptive Stream Mining


Adaptive Stream Mining
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Author : Albert Bifet
language : en
Publisher: IOS Press
Release Date : 2010

Adaptive Stream Mining written by Albert Bifet and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.


This book is a significant contribution to the subject of mining time-changing data streams and addresses the design of learning algorithms for this purpose. It introduces new contributions on several different aspects of the problem, identifying research opportunities and increasing the scope for applications. It also includes an in-depth study of stream mining and a theoretical analysis of proposed methods and algorithms. The first section is concerned with the use of an adaptive sliding window algorithm (ADWIN). Since this has rigorous performance guarantees, using it in place of counters or accumulators, it offers the possibility of extending such guarantees to learning and mining algorithms not initially designed for drifting data. Testing with several methods, including Naïve Bayes, clustering, decision trees and ensemble methods, is discussed as well. The second part of the book describes a formal study of connected acyclic graphs, or 'trees', from the point of view of closure-based mining, presenting efficient algorithms for subtree testing and for mining ordered and unordered frequent closed trees. Lastly, a general methodology to identify closed patterns in a data stream is outlined. This is applied to develop an incremental method, a sliding-window based method, and a method that mines closed trees adaptively from data streams. These are used to introduce classification methods for tree data streams.



Machine Learning For Data Streams


Machine Learning For Data Streams
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Author : Albert Bifet
language : en
Publisher: MIT Press
Release Date : 2023-05-09

Machine Learning For Data Streams written by Albert Bifet and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-09 with Computers categories.


A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.



Data Mining In Time Series And Streaming Databases


Data Mining In Time Series And Streaming Databases
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Author : Last Mark
language : en
Publisher: World Scientific
Release Date : 2018-01-11

Data Mining In Time Series And Streaming Databases written by Last Mark and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-11 with Computers categories.


This compendium is a completely revised version of an earlier book, Data Mining in Time Series Databases, by the same editors. It provides a unique collection of new articles written by leading experts that account for the latest developments in the field of time series and data stream mining. The emerging topics covered by the book include weightless neural modeling for mining data streams, using ensemble classifiers for imbalanced and evolving data streams, document stream mining with active learning, and many more. In particular, it addresses the domain of streaming data, which has recently become one of the emerging topics in Data Science, Big Data, and related areas. Existing titles do not provide sufficient information on this topic. Contents: Streaming Data Mining with Massive Online Analytics (MOA) (Albert Bifet, Jesse Read, Geoff Holmes and Bernhard Pfahringer)Weightless Neural Modeling for Mining Data Streams (Douglas O Cardoso, João Gama and Felipe França)Ensemble Classifiers for Imbalanced and Evolving Data Streams (Dariusz Brzezinski and Jerzy Stefanowski)Consensus Learning for Sequence Data (Andreas Nienkötter and Xiaoyi Jiang)Clustering-Based Classification of Document Streams with Active Learning (Mark Last, Maxim Stoliar and Menahem Friedman)Supporting the Mining of Big Data by Means of Domain Knowledge During the Pre-mining Phases (Rémon Cornelisse and Sunil Choenni)Data Analytics: Industrial Perspective & Solutions for Streaming Data (Mohsin Munir, Sebastian Baumbach, Ying Gu, Andreas Dengel and Sheraz Ahmed) Readership: Researchers, academics, professionals and graduate students in artificial intelligence, machine learning, databases, and information science. Keywords: Time Series;Data Streams;Big Data;Internet of Things;Concept Drift;Sequence Mining;Episode Mining;Incremental Learning;Active LearningReview:0



Knowledge Discovery From Data Streams


Knowledge Discovery From Data Streams
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Author : Joao Gama
language : en
Publisher: CRC Press
Release Date : 2010-05-25

Knowledge Discovery From Data Streams written by Joao Gama and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-25 with Business & Economics categories.


Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents



Frequent Pattern Mining


Frequent Pattern Mining
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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2014-08-29

Frequent Pattern Mining written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-29 with Computers categories.


This comprehensive reference consists of 18 chapters from prominent researchers in the field. Each chapter is self-contained, and synthesizes one aspect of frequent pattern mining. An emphasis is placed on simplifying the content, so that students and practitioners can benefit from the book. Each chapter contains a survey describing key research on the topic, a case study and future directions. Key topics include: Pattern Growth Methods, Frequent Pattern Mining in Data Streams, Mining Graph Patterns, Big Data Frequent Pattern Mining, Algorithms for Data Clustering and more. Advanced-level students in computer science, researchers and practitioners from industry will find this book an invaluable reference.



Stream Data Mining Algorithms And Their Probabilistic Properties


Stream Data Mining Algorithms And Their Probabilistic Properties
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Author : Leszek Rutkowski
language : en
Publisher: Springer
Release Date : 2019-03-16

Stream Data Mining Algorithms And Their Probabilistic Properties written by Leszek Rutkowski and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Technology & Engineering categories.


This book presents a unique approach to stream data mining. Unlike the vast majority of previous approaches, which are largely based on heuristics, it highlights methods and algorithms that are mathematically justified. First, it describes how to adapt static decision trees to accommodate data streams; in this regard, new splitting criteria are developed to guarantee that they are asymptotically equivalent to the classical batch tree. Moreover, new decision trees are designed, leading to the original concept of hybrid trees. In turn, nonparametric techniques based on Parzen kernels and orthogonal series are employed to address concept drift in the problem of non-stationary regressions and classification in a time-varying environment. Lastly, an extremely challenging problem that involves designing ensembles and automatically choosing their sizes is described and solved. Given its scope, the book is intended for a professional audience of researchers and practitioners who deal with stream data, e.g. in telecommunication, banking, and sensor networks.



Encyclopedia Of Business Analytics And Optimization


Encyclopedia Of Business Analytics And Optimization
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Author : Wang, John
language : en
Publisher: IGI Global
Release Date : 2014-02-28

Encyclopedia Of Business Analytics And Optimization written by Wang, John and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-28 with Business & Economics categories.


As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.



Encyclopedia Of Information Science And Technology Fifth Edition


Encyclopedia Of Information Science And Technology Fifth Edition
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Author : Khosrow-Pour D.B.A., Mehdi
language : en
Publisher: IGI Global
Release Date : 2020-07-24

Encyclopedia Of Information Science And Technology Fifth Edition written by Khosrow-Pour D.B.A., Mehdi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-24 with Computers categories.


The rise of intelligence and computation within technology has created an eruption of potential applications in numerous professional industries. Techniques such as data analysis, cloud computing, machine learning, and others have altered the traditional processes of various disciplines including healthcare, economics, transportation, and politics. Information technology in today’s world is beginning to uncover opportunities for experts in these fields that they are not yet aware of. The exposure of specific instances in which these devices are being implemented will assist other specialists in how to successfully utilize these transformative tools with the appropriate amount of discretion, safety, and awareness. Considering the level of diverse uses and practices throughout the globe, the fifth edition of the Encyclopedia of Information Science and Technology series continues the enduring legacy set forth by its predecessors as a premier reference that contributes the most cutting-edge concepts and methodologies to the research community. The Encyclopedia of Information Science and Technology, Fifth Edition is a three-volume set that includes 136 original and previously unpublished research chapters that present multidisciplinary research and expert insights into new methods and processes for understanding modern technological tools and their applications as well as emerging theories and ethical controversies surrounding the field of information science. Highlighting a wide range of topics such as natural language processing, decision support systems, and electronic government, this book offers strategies for implementing smart devices and analytics into various professional disciplines. The techniques discussed in this publication are ideal for IT professionals, developers, computer scientists, practitioners, managers, policymakers, engineers, data analysts, and programmers seeking to understand the latest developments within this field and who are looking to apply new tools and policies in their practice. Additionally, academicians, researchers, and students in fields that include but are not limited to software engineering, cybersecurity, information technology, media and communications, urban planning, computer science, healthcare, economics, environmental science, data management, and political science will benefit from the extensive knowledge compiled within this publication.



Smart Intelligent Computing And Applications


Smart Intelligent Computing And Applications
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Author : Suresh Chandra Satapathy
language : en
Publisher: Springer
Release Date : 2018-11-04

Smart Intelligent Computing And Applications written by Suresh Chandra Satapathy and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-04 with Technology & Engineering categories.


The proceedings covers advanced and multi-disciplinary research on design of smart computing and informatics. The theme of the book broadly focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solution to varied problems in society, environment and industries. The volume publishes quality work pertaining to the scope of the conference which is extended towards deployment of emerging computational and knowledge transfer approaches, optimizing solutions in varied disciplines of science, technology and healthcare.



Cyber Physical Systems


Cyber Physical Systems
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Author : Alla G. Kravets
language : en
Publisher: Springer Nature
Release Date : 2021-04-13

Cyber Physical Systems written by Alla G. Kravets and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-13 with Technology & Engineering categories.


This book offers ideas to help improve digital technologies and increase their efficiency during implementation and application for researchers and practitioners. The outstanding position of the book among others is that it dwells with cyber-physical systems’ progress and proposes ideas and finding around digital tools and technologies and their application. A distinguished contribution is in presenting results on Digital Twins development and application, enhancing approaches of communication and information transferring between cyber-physical systems connected within the Internet of things platforms, computer linguistic as a part of cyber-physical systems, intelligent cybersecurity and computer vision systems. The target audience of this book also includes practitioners and experts, as well as state authorities and representatives of manufacturing and industry who are interested in creating and implementing of cyber-physical systems in framework of digitalization projects.