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Machine Learning and Knowledge Extraction

Author: Andreas Holzinger

Publisher: Springer Nature

Published: 2020-08-19

Total Pages: 552

ISBN-13: 3030573214

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This book constitutes the refereed proceedings of the 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, held in Dublin, Ireland, in August 2020. The 30 revised full papers presented were carefully reviewed and selected from 140 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity. Due to the Corona pandemic CD-MAKE 2020 was held as a virtual event.

Book Synopsis Machine Learning and Knowledge Extraction by : Andreas Holzinger

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer Nature. This book was released on 2020-08-19 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, held in Dublin, Ireland, in August 2020. The 30 revised full papers presented were carefully reviewed and selected from 140 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity. Due to the Corona pandemic CD-MAKE 2020 was held as a virtual event.

Machine Learning and Knowledge Extraction

Author: Andreas Holzinger

Publisher: Springer

Published: 2018-08-23

Total Pages: 379

ISBN-13: 3319997408

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This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2018, held in Hamburg, Germany, in September 2018. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are clustered under the following topical sections: MAKE-Main Track, MAKE-Text, MAKE-Smart Factory, MAKE-Topology, and MAKE Explainable AI.

Book Synopsis Machine Learning and Knowledge Extraction by : Andreas Holzinger

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer. This book was released on 2018-08-23 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2018, held in Hamburg, Germany, in September 2018. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The papers are clustered under the following topical sections: MAKE-Main Track, MAKE-Text, MAKE-Smart Factory, MAKE-Topology, and MAKE Explainable AI.

Machine Learning and Knowledge Extraction

Author: Andreas Holzinger

Publisher: Springer Nature

Published: 2019-08-22

Total Pages: 428

ISBN-13: 3030297268

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This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Book Synopsis Machine Learning and Knowledge Extraction by : Andreas Holzinger

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer Nature. This book was released on 2019-08-22 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the IFIP TC 5, TC 12, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2019, held in Canterbury, UK, in August 2019. The 25 revised full papers presented were carefully reviewed and selected from 45 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Machine Learning and Knowledge Extraction

Author: Andreas Holzinger

Publisher: Springer Nature

Published: 2021-08-11

Total Pages: 366

ISBN-13: 3030840603

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This book constitutes the refereed proceedings of the 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, held in virtually in August 2021. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 48 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Book Synopsis Machine Learning and Knowledge Extraction by : Andreas Holzinger

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer Nature. This book was released on 2021-08-11 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2021, held in virtually in August 2021. The 20 full papers and 2 short papers presented were carefully reviewed and selected from 48 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity.

Towards Integrative Machine Learning and Knowledge Extraction

Author: Andreas Holzinger

Publisher: Springer

Published: 2017-10-27

Total Pages: 207

ISBN-13: 3319697757

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The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

Book Synopsis Towards Integrative Machine Learning and Knowledge Extraction by : Andreas Holzinger

Download or read book Towards Integrative Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer. This book was released on 2017-10-27 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: The BIRS Workshop “Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets” (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of “hot topics” toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

Machine Learning and Knowledge Extraction

Author: Andreas Holzinger

Publisher: Springer Nature

Published: 2023-08-21

Total Pages: 335

ISBN-13: 3031408373

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This volume LNCS-IFIP constitutes the refereed proceedings of the 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2023 in Benevento, Italy, during August 28 – September 1, 2023. The 18 full papers presented together were carefully reviewed and selected from 30 submissions. The conference focuses on integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.

Book Synopsis Machine Learning and Knowledge Extraction by : Andreas Holzinger

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer Nature. This book was released on 2023-08-21 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume LNCS-IFIP constitutes the refereed proceedings of the 7th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2023 in Benevento, Italy, during August 28 – September 1, 2023. The 18 full papers presented together were carefully reviewed and selected from 30 submissions. The conference focuses on integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.

Machine Learning and Knowledge Extraction

Author: Andreas Holzinger

Publisher: Springer Nature

Published: 2022-08-10

Total Pages: 390

ISBN-13: 3031144635

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This book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022. The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.

Book Synopsis Machine Learning and Knowledge Extraction by : Andreas Holzinger

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer Nature. This book was released on 2022-08-10 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 6th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2022, held in Vienna, Austria during August 2022. The 23 full papers presented were carefully reviewed and selected from 45 submissions. The papers are covering a wide range from integrative machine learning approach, considering the importance of data science and visualization for the algorithmic pipeline with a strong emphasis on privacy, data protection, safety and security.

Signal Processing Techniques for Knowledge Extraction and Information Fusion

Author: Danilo Mandic

Publisher: Springer Science & Business Media

Published: 2008-03-23

Total Pages: 335

ISBN-13: 0387743677

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This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.

Book Synopsis Signal Processing Techniques for Knowledge Extraction and Information Fusion by : Danilo Mandic

Download or read book Signal Processing Techniques for Knowledge Extraction and Information Fusion written by Danilo Mandic and published by Springer Science & Business Media. This book was released on 2008-03-23 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the latest research achievements from signal processing and related disciplines, consolidating existing and proposed directions in DSP-based knowledge extraction and information fusion. The book includes contributions presenting both novel algorithms and existing applications, emphasizing on-line processing of real-world data. Readers discover applications that solve biomedical, industrial, and environmental problems.

Machine Learning and Knowledge Extraction

Author: Andreas Holzinger

Publisher: Springer

Published: 2017-08-23

Total Pages: 383

ISBN-13: 3319668080

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This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017. The 24 revised full papers presented were carefully reviewed and selected for inclusion in this volume. The papers deal with fundamental questions and theoretical aspects and cover a wide range of topics in the field of machine learning and knowledge extraction. They are organized in the following topical sections: MAKE topology; MAKE smart factory; MAKE privacy; MAKE VIS; MAKE AAL; and MAKE semantics.

Book Synopsis Machine Learning and Knowledge Extraction by : Andreas Holzinger

Download or read book Machine Learning and Knowledge Extraction written by Andreas Holzinger and published by Springer. This book was released on 2017-08-23 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017. The 24 revised full papers presented were carefully reviewed and selected for inclusion in this volume. The papers deal with fundamental questions and theoretical aspects and cover a wide range of topics in the field of machine learning and knowledge extraction. They are organized in the following topical sections: MAKE topology; MAKE smart factory; MAKE privacy; MAKE VIS; MAKE AAL; and MAKE semantics.

Adaptive Web Sites

Author: Juan D. Velásquez

Publisher: IOS Press

Published: 2008

Total Pages: 296

ISBN-13: 1586038311

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This book can be presented in two different ways. Firstly, it introduces a particular methodology to build adaptive Web sites and secondly, it presents the main concepts behind Web mining and then applying them to adaptive Web sites. In this case, Adaptive Web Sites is the case study to exemplify the tools introduced in the text. The authors start by introducing the Web and motivating the need for adaptive Web sites. The second chapter introduces the main concepts behind a Web site: its operation, its associated data and structure, user sessions, etc. Chapter three explains the Web mining process and the tools to analyze Web data, mainly focused in machine learning. The fourth chapter looks at how to store and manage data. Chapter five looks at the three main and different mining tasks: content, links and usage. The following chapter covers Web personalization; a crucial topic if we want to adapt our site to specific groups of people. Chapter seven shows how to use information extraction techniques to find user behavior patterns. The subsequent chapter explains how to acquire and maintain knowledge extracted from the previous phase. Finally, chapter nine contains the case study where all the previous concepts are applied to present a framework to build adaptive Web sites. In other words, the authors have taken care of writing a self-contained book for people that want to learn and apply personalization and adaptation in Web sites. This is commendable considering the large and increasing bibliography in these and related topics. The writing is easy to follow and although the coverage is not exhaustive, the main concepts and topics are all covered.

Book Synopsis Adaptive Web Sites by : Juan D. Velásquez

Download or read book Adaptive Web Sites written by Juan D. Velásquez and published by IOS Press. This book was released on 2008 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book can be presented in two different ways. Firstly, it introduces a particular methodology to build adaptive Web sites and secondly, it presents the main concepts behind Web mining and then applying them to adaptive Web sites. In this case, Adaptive Web Sites is the case study to exemplify the tools introduced in the text. The authors start by introducing the Web and motivating the need for adaptive Web sites. The second chapter introduces the main concepts behind a Web site: its operation, its associated data and structure, user sessions, etc. Chapter three explains the Web mining process and the tools to analyze Web data, mainly focused in machine learning. The fourth chapter looks at how to store and manage data. Chapter five looks at the three main and different mining tasks: content, links and usage. The following chapter covers Web personalization; a crucial topic if we want to adapt our site to specific groups of people. Chapter seven shows how to use information extraction techniques to find user behavior patterns. The subsequent chapter explains how to acquire and maintain knowledge extracted from the previous phase. Finally, chapter nine contains the case study where all the previous concepts are applied to present a framework to build adaptive Web sites. In other words, the authors have taken care of writing a self-contained book for people that want to learn and apply personalization and adaptation in Web sites. This is commendable considering the large and increasing bibliography in these and related topics. The writing is easy to follow and although the coverage is not exhaustive, the main concepts and topics are all covered.