Knowledge Discovery from Data Streams

Knowledge Discovery from Data Streams

Author: Joao Gama

Publisher: CRC Press

Published: 2010-05-25

Total Pages: 256

ISBN-13: 1439826129

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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


Book Synopsis Knowledge Discovery from Data Streams by : Joao Gama

Download or read book Knowledge Discovery from Data Streams written by Joao Gama and published by CRC Press. This book was released on 2010-05-25 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Data Streams

Data Streams

Author: Charu C. Aggarwal

Publisher: Springer Science & Business Media

Published: 2007-04-03

Total Pages: 365

ISBN-13: 0387475346

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This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions. The book is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.


Book Synopsis Data Streams by : Charu C. Aggarwal

Download or read book Data Streams written by Charu C. Aggarwal and published by Springer Science & Business Media. This book was released on 2007-04-03 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject. This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions. The book is intended for a professional audience composed of researchers and practitioners in industry. This book is also appropriate for advanced-level students in computer science.

Web Semantics for Textual and Visual Information Retrieval

Web Semantics for Textual and Visual Information Retrieval

Author: Singh, Aarti

Publisher: IGI Global

Published: 2017-02-22

Total Pages: 290

ISBN-13: 1522524843

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Modern society exists in a digital era in which high volumes of multimedia information exists. To optimize the management of this data, new methods are emerging for more efficient information retrieval. Web Semantics for Textual and Visual Information Retrieval is a pivotal reference source for the latest academic research on embedding and associating semantics with multimedia information to improve data retrieval techniques. Highlighting a range of pertinent topics such as automation, knowledge discovery, and social networking, this book is ideally designed for researchers, practitioners, students, and professionals interested in emerging trends in information retrieval.


Book Synopsis Web Semantics for Textual and Visual Information Retrieval by : Singh, Aarti

Download or read book Web Semantics for Textual and Visual Information Retrieval written by Singh, Aarti and published by IGI Global. This book was released on 2017-02-22 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern society exists in a digital era in which high volumes of multimedia information exists. To optimize the management of this data, new methods are emerging for more efficient information retrieval. Web Semantics for Textual and Visual Information Retrieval is a pivotal reference source for the latest academic research on embedding and associating semantics with multimedia information to improve data retrieval techniques. Highlighting a range of pertinent topics such as automation, knowledge discovery, and social networking, this book is ideally designed for researchers, practitioners, students, and professionals interested in emerging trends in information retrieval.

Data Streams

Data Streams

Author: S. Muthukrishnan

Publisher: Now Publishers Inc

Published: 2005

Total Pages: 136

ISBN-13: 193301914X

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In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges.


Book Synopsis Data Streams by : S. Muthukrishnan

Download or read book Data Streams written by S. Muthukrishnan and published by Now Publishers Inc. This book was released on 2005 with total page 136 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the data stream scenario, input arrives very rapidly and there is limited memory to store the input. Algorithms have to work with one or few passes over the data, space less than linear in the input size or time significantly less than the input size. In the past few years, a new theory has emerged for reasoning about algorithms that work within these constraints on space, time, and number of passes. Some of the methods rely on metric embeddings, pseudo-random computations, sparse approximation theory and communication complexity. The applications for this scenario include IP network traffic analysis, mining text message streams and processing massive data sets in general. Researchers in Theoretical Computer Science, Databases, IP Networking and Computer Systems are working on the data stream challenges.

Discovery Science

Discovery Science

Author: Bernahrd Pfahringer

Publisher: Springer

Published: 2010-11-02

Total Pages: 384

ISBN-13: 3642161847

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Annotation. This book constitutes the refereed proceedings of the 13th International Conference on Discovery Science, DS 2010, held in Canberra, Australia, in October 2010. The 25 revised full papers presented were carefully selected from 43 submissions and include the first part of the book. In a second part invited talks of ALT 2010 and DS 2010 are presented. The scope of the conference is the exchange of new ideas and information among researchers working in the area of automatic scientific discovery or working on tools for supporting the human process of discovery in science.


Book Synopsis Discovery Science by : Bernahrd Pfahringer

Download or read book Discovery Science written by Bernahrd Pfahringer and published by Springer. This book was released on 2010-11-02 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Annotation. This book constitutes the refereed proceedings of the 13th International Conference on Discovery Science, DS 2010, held in Canberra, Australia, in October 2010. The 25 revised full papers presented were carefully selected from 43 submissions and include the first part of the book. In a second part invited talks of ALT 2010 and DS 2010 are presented. The scope of the conference is the exchange of new ideas and information among researchers working in the area of automatic scientific discovery or working on tools for supporting the human process of discovery in science.

Learning from Data Streams

Learning from Data Streams

Author: João Gama

Publisher: Springer Science & Business Media

Published: 2007-10-11

Total Pages: 486

ISBN-13: 3540736786

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Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.


Book Synopsis Learning from Data Streams by : João Gama

Download or read book Learning from Data Streams written by João Gama and published by Springer Science & Business Media. This book was released on 2007-10-11 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Social Network Analytics for Contemporary Business Organizations

Social Network Analytics for Contemporary Business Organizations

Author: Bansal, Himani

Publisher: IGI Global

Published: 2018-03-23

Total Pages: 321

ISBN-13: 1522550984

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Social technology is quickly becoming a vital tool in our personal, educational, and professional lives. Its use must be further examined in order to determine the role of social media technology in organizational settings to promote business development and growth. Social Network Analytics for Contemporary Business Organizations is a critical scholarly resource that analyzes the application of social media in business applications. Featuring coverage on a broad range of topics, such as business management, dynamic networks, and online interaction, this book is geared towards professionals, researchers, academics, students, managers, and practitioners actively involved in the business industry.


Book Synopsis Social Network Analytics for Contemporary Business Organizations by : Bansal, Himani

Download or read book Social Network Analytics for Contemporary Business Organizations written by Bansal, Himani and published by IGI Global. This book was released on 2018-03-23 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: Social technology is quickly becoming a vital tool in our personal, educational, and professional lives. Its use must be further examined in order to determine the role of social media technology in organizational settings to promote business development and growth. Social Network Analytics for Contemporary Business Organizations is a critical scholarly resource that analyzes the application of social media in business applications. Featuring coverage on a broad range of topics, such as business management, dynamic networks, and online interaction, this book is geared towards professionals, researchers, academics, students, managers, and practitioners actively involved in the business industry.

Machine Learning Techniques for Improved Business Analytics

Machine Learning Techniques for Improved Business Analytics

Author: Dileep Kumar G

Publisher: Business Science Reference

Published: 2018-12-13

Total Pages: 308

ISBN-13: 9781522588511

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"This book provides the information on the machine learning techniques that can be in business problems in efficient way. It encourages the data Scientists to take a proactive attitude toward applying machine learning techniques in business. It increases evolutionary computation awareness in Machine Learning by providing a clear direction for applying machine learning techniques in Business Industry"--


Book Synopsis Machine Learning Techniques for Improved Business Analytics by : Dileep Kumar G

Download or read book Machine Learning Techniques for Improved Business Analytics written by Dileep Kumar G and published by Business Science Reference. This book was released on 2018-12-13 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book provides the information on the machine learning techniques that can be in business problems in efficient way. It encourages the data Scientists to take a proactive attitude toward applying machine learning techniques in business. It increases evolutionary computation awareness in Machine Learning by providing a clear direction for applying machine learning techniques in Business Industry"--

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Machine Learning and Knowledge Discovery for Engineering Systems Health Management

Author: Ashok N. Srivastava

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 489

ISBN-13: 1439841799

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This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.


Book Synopsis Machine Learning and Knowledge Discovery for Engineering Systems Health Management by : Ashok N. Srivastava

Download or read book Machine Learning and Knowledge Discovery for Engineering Systems Health Management written by Ashok N. Srivastava and published by CRC Press. This book was released on 2016-04-19 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.

Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Author: Honghua Dai

Publisher: Springer Science & Business Media

Published: 2004-05-11

Total Pages: 731

ISBN-13: 354022064X

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This book constitutes the refereed proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data mining, PAKDD 2004, held in Sydney, Australia in May 2004. The 50 revised full papers and 31 revised short papers presented were carefully reviewed and selected from a total of 238 submissions. The papers are organized in topical sections on classification; clustering; association rules; novel algorithms; event mining, anomaly detection, and intrusion detection; ensemble learning; Bayesian network and graph mining; text mining; multimedia mining; text mining and Web mining; statistical methods, sequential data mining, and time series mining; and biomedical data mining.


Book Synopsis Advances in Knowledge Discovery and Data Mining by : Honghua Dai

Download or read book Advances in Knowledge Discovery and Data Mining written by Honghua Dai and published by Springer Science & Business Media. This book was released on 2004-05-11 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th Pacific-Asia Conference on Knowledge Discovery and Data mining, PAKDD 2004, held in Sydney, Australia in May 2004. The 50 revised full papers and 31 revised short papers presented were carefully reviewed and selected from a total of 238 submissions. The papers are organized in topical sections on classification; clustering; association rules; novel algorithms; event mining, anomaly detection, and intrusion detection; ensemble learning; Bayesian network and graph mining; text mining; multimedia mining; text mining and Web mining; statistical methods, sequential data mining, and time series mining; and biomedical data mining.