Knowledge Discovery In Databases Pkdd 2005

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Knowledge Discovery in Databases: PKDD 2005

Author : Alípio Jorge
Publisher : Springer Science & Business Media
ISBN 13 : 3540292446
Total Pages : 738 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Knowledge Discovery in Databases: PKDD 2005 by : Alípio Jorge

Download or read book Knowledge Discovery in Databases: PKDD 2005 written by Alípio Jorge and published by Springer Science & Business Media. This book was released on 2005-09-26 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work required a tremendous e?ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qua- ?edindependentreviewsperpaper(withveryfewexceptions)andoneadditional overall input from one of the Area Chairs. After the authors’ responses and the online discussions for many of the papers, we arrived at the ?nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall. We thank all involved for all the e?ort with reviewing and selection of papers. Besidesthecoretechnicalprogram,ECMLandPKDDhad6invitedspeakers, 10 workshops, 8 tutorials and a Knowledge Discovery Challenge.

Knowledge Discovery in Databases: PKDD 2005

Author : Alípio Jorge
Publisher : Springer
ISBN 13 : 3540316655
Total Pages : 738 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Knowledge Discovery in Databases: PKDD 2005 by : Alípio Jorge

Download or read book Knowledge Discovery in Databases: PKDD 2005 written by Alípio Jorge and published by Springer. This book was released on 2005-11-07 with total page 738 pages. Available in PDF, EPUB and Kindle. Book excerpt: The European Conference on Machine Learning (ECML) and the European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) were jointly organized this year for the ?fth time in a row, after some years of mutual independence before. After Freiburg (2001), Helsinki (2002), Cavtat (2003) and Pisa (2004), Porto received the 16th edition of ECML and the 9th PKDD in October 3–7. Having the two conferences together seems to be working well: 585 di?erent paper submissions were received for both events, which maintains the high s- mission standard of last year. Of these, 335 were submitted to ECML only, 220 to PKDD only and 30 to both. Such a high volume of scienti?c work required a tremendous e?ort from Area Chairs, Program Committee members and some additional reviewers. On average, PC members had 10 papers to evaluate, and Area Chairs had 25 papers to decide upon. We managed to have 3 highly qua- ?edindependentreviewsperpaper(withveryfewexceptions)andoneadditional overall input from one of the Area Chairs. After the authors’ responses and the online discussions for many of the papers, we arrived at the ?nal selection of 40 regular papers for ECML and 35 for PKDD. Besides these, 32 others were accepted as short papers for ECML and 35 for PKDD. This represents a joint acceptance rate of around 13% for regular papers and 25% overall. We thank all involved for all the e?ort with reviewing and selection of papers. Besidesthecoretechnicalprogram,ECMLandPKDDhad6invitedspeakers, 10 workshops, 8 tutorials and a Knowledge Discovery Challenge.

Knowledge Discovery in Databases: PKDD 2006

Author : Johannes Fürnkranz
Publisher : Springer Science & Business Media
ISBN 13 : 3540453741
Total Pages : 681 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Knowledge Discovery in Databases: PKDD 2006 by : Johannes Fürnkranz

Download or read book Knowledge Discovery in Databases: PKDD 2006 written by Johannes Fürnkranz and published by Springer Science & Business Media. This book was released on 2006-09-15 with total page 681 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2006. The book presents 36 revised full papers and 26 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers offer a wealth of new results in knowledge discovery in databases and address all current issues in the area.

Knowledge Discovery in Databases

Author : Nada Lavra
Publisher :
ISBN 13 : 9783662164013
Total Pages : 530 pages
Book Rating : 4.1/5 (64 download)

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Book Synopsis Knowledge Discovery in Databases by : Nada Lavra

Download or read book Knowledge Discovery in Databases written by Nada Lavra and published by . This book was released on 2014-09-01 with total page 530 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Knowledge Discovery in Databases: PKDD 2004

Author : Jean-Francois Boulicaut
Publisher : Springer Science & Business Media
ISBN 13 : 3540231080
Total Pages : 578 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Knowledge Discovery in Databases: PKDD 2004 by : Jean-Francois Boulicaut

Download or read book Knowledge Discovery in Databases: PKDD 2004 written by Jean-Francois Boulicaut and published by Springer Science & Business Media. This book was released on 2004-09-10 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2004, held in Pisa, Italy, in September 2004 jointly with ECML 2004. The 39 revised full papers and 9 revised short papers presented together with abstracts of 5 invited talks were carefully reviewed and selected from 194 papers submitted to PKDD and 107 papers submitted to both, PKDD and ECML. The papers present a wealth of new results in knowledge discovery in databases and address all current issues in the area.

Principles of Data Mining and Knowledge Discovery

Author : Jan Komorowski
Publisher : Springer Science & Business Media
ISBN 13 : 9783540632238
Total Pages : 420 pages
Book Rating : 4.6/5 (322 download)

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Book Synopsis Principles of Data Mining and Knowledge Discovery by : Jan Komorowski

Download or read book Principles of Data Mining and Knowledge Discovery written by Jan Komorowski and published by Springer Science & Business Media. This book was released on 1997-06-13 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD '97, held in Trondheim, Norway, in June 1997. The volume presents a total of 38 revised full papers together with abstracts of one invited talk and four tutorials. Among the topics covered are data and knowledge representation, statistical and probabilistic methods, logic-based approaches, man-machine interaction aspects, AI contributions, high performance computing support, machine learning, automated scientific discovery, quality assessment, and applications.

Knowledge Discovery in Databases

Author :
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (116 download)

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Book Synopsis Knowledge Discovery in Databases by :

Download or read book Knowledge Discovery in Databases written by and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Knowledge Discovery in Inductive Databases

Author : Francesco Bonchi
Publisher : Springer
ISBN 13 : 3540332936
Total Pages : 259 pages
Book Rating : 4.5/5 (43 download)

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Book Synopsis Knowledge Discovery in Inductive Databases by : Francesco Bonchi

Download or read book Knowledge Discovery in Inductive Databases written by Francesco Bonchi and published by Springer. This book was released on 2006-03-05 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the thoroughly refereed joint postproceedings of the 4th International Workshop on Knowledge Discovery in Inductive Databases, October 2005. 20 revised full papers presented together with 2 are reproduced here. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.

Knowledge Discovery in Inductive Databases

Author : Saso Dzeroski
Publisher : Springer
ISBN 13 : 3540755497
Total Pages : 301 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Knowledge Discovery in Inductive Databases by : Saso Dzeroski

Download or read book Knowledge Discovery in Inductive Databases written by Saso Dzeroski and published by Springer. This book was released on 2007-09-29 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed joint postproceedings of the 5th International Workshop on Knowledge Discovery in Inductive Databases, KDID 2006, held in association with ECML/PKDD. Bringing together the fields of databases, machine learning, and data mining, the papers address various current topics in knowledge discovery and data mining in the framework of inductive databases such as constraint-based mining, database technology and inductive querying.

Machine Learning: ECML 2005

Author : João Gama
Publisher : Springer Science & Business Media
ISBN 13 : 3540292438
Total Pages : 784 pages
Book Rating : 4.5/5 (42 download)

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Book Synopsis Machine Learning: ECML 2005 by : João Gama

Download or read book Machine Learning: ECML 2005 written by João Gama and published by Springer Science & Business Media. This book was released on 2005-09-22 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th European Conference on Machine Learning, ECML 2005, jointly held with PKDD 2005 in Porto, Portugal, in October 2005. The 40 revised full papers and 32 revised short papers presented together with abstracts of 6 invited talks were carefully reviewed and selected from 335 papers submitted to ECML and 30 papers submitted to both, ECML and PKDD. The papers present a wealth of new results in the area and address all current issues in machine learning.

Learning from Imbalanced Data Sets

Author : Alberto Fernández
Publisher : Springer
ISBN 13 : 3319980742
Total Pages : 377 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Learning from Imbalanced Data Sets by : Alberto Fernández

Download or read book Learning from Imbalanced Data Sets written by Alberto Fernández and published by Springer. This book was released on 2018-10-22 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a general and comprehensible overview of imbalanced learning. It contains a formal description of a problem, and focuses on its main features, and the most relevant proposed solutions. Additionally, it considers the different scenarios in Data Science for which the imbalanced classification can create a real challenge. This book stresses the gap with standard classification tasks by reviewing the case studies and ad-hoc performance metrics that are applied in this area. It also covers the different approaches that have been traditionally applied to address the binary skewed class distribution. Specifically, it reviews cost-sensitive learning, data-level preprocessing methods and algorithm-level solutions, taking also into account those ensemble-learning solutions that embed any of the former alternatives. Furthermore, it focuses on the extension of the problem for multi-class problems, where the former classical methods are no longer to be applied in a straightforward way. This book also focuses on the data intrinsic characteristics that are the main causes which, added to the uneven class distribution, truly hinders the performance of classification algorithms in this scenario. Then, some notes on data reduction are provided in order to understand the advantages related to the use of this type of approaches. Finally this book introduces some novel areas of study that are gathering a deeper attention on the imbalanced data issue. Specifically, it considers the classification of data streams, non-classical classification problems, and the scalability related to Big Data. Examples of software libraries and modules to address imbalanced classification are provided. This book is highly suitable for technical professionals, senior undergraduate and graduate students in the areas of data science, computer science and engineering. It will also be useful for scientists and researchers to gain insight on the current developments in this area of study, as well as future research directions.

Statistical Implicative Analysis

Author : Régis Gras
Publisher : Springer
ISBN 13 : 3540789839
Total Pages : 513 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Statistical Implicative Analysis by : Régis Gras

Download or read book Statistical Implicative Analysis written by Régis Gras and published by Springer. This book was released on 2008-07-06 with total page 513 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical implicative analysis is a data analysis method created by Régis Gras almost thirty years ago which has a significant impact on a variety of areas ranging from pedagogical and psychological research to data mining. Statistical implicative analysis (SIA) provides a framework for evaluating the strength of implications; such implications are formed through common knowledge acquisition techniques in any learning process, human or artificial. This new concept has developed into a unifying methodology, and has generated a powerful convergence of thought between mathematicians, statisticians, psychologists, specialists in pedagogy and last, but not least, computer scientists specialized in data mining. This volume collects significant research contributions of several rather distinct disciplines that benefit from SIA. Contributions range from psychological and pedagogical research, bioinformatics, knowledge management, and data mining.

Machine Learning and Data Mining in Pattern Recognition

Author : Petra Perner
Publisher : Springer Science & Business Media
ISBN 13 : 3540734988
Total Pages : 927 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Machine Learning and Data Mining in Pattern Recognition by : Petra Perner

Download or read book Machine Learning and Data Mining in Pattern Recognition written by Petra Perner and published by Springer Science & Business Media. This book was released on 2007-07-16 with total page 927 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ever wondered what the state of the art is in machine learning and data mining? Well, now you can find out. This book constitutes the refereed proceedings of the 5th International Conference on Machine Learning and Data Mining in Pattern Recognition, held in Leipzig, Germany, in July 2007. The 66 revised full papers presented together with 1 invited talk were carefully reviewed and selected from more than 250 submissions. The papers are organized in topical sections.

Machine Learning for Data Streams

Author : Albert Bifet
Publisher : MIT Press
ISBN 13 : 026254783X
Total Pages : 289 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Machine Learning for Data Streams by : Albert Bifet

Download or read book Machine Learning for Data Streams written by Albert Bifet and published by MIT Press. This book was released on 2023-05-09 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Knowledge Discovery in Databases: PKDD 2006

Author : Johannes Fürnkranz
Publisher : Springer
ISBN 13 : 9783540830702
Total Pages : 660 pages
Book Rating : 4.8/5 (37 download)

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Book Synopsis Knowledge Discovery in Databases: PKDD 2006 by : Johannes Fürnkranz

Download or read book Knowledge Discovery in Databases: PKDD 2006 written by Johannes Fürnkranz and published by Springer. This book was released on 2009-09-02 with total page 660 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2006. The book presents 36 revised full papers and 26 revised short papers together with abstracts of 5 invited talks, carefully reviewed and selected from 564 papers submitted. The papers offer a wealth of new results in knowledge discovery in databases and address all current issues in the area.

Semantics, Web and Mining

Author : Markus Ackermann
Publisher : Springer
ISBN 13 : 3540476989
Total Pages : 196 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Semantics, Web and Mining by : Markus Ackermann

Download or read book Semantics, Web and Mining written by Markus Ackermann and published by Springer. This book was released on 2006-11-28 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed and extended post-proceedings of the joint European Web Mining Forum, EWMF 2005, and the International Workshop on Knowledge Discovery and Ontologies, KDO 2005, held in association with ECML/PKDD in Porto, Portugal in October 2005. The 10 revised full papers presented together with one invited paper and one particularly fitting contribution from KDO 2004 were carefully selected for inclusion in the book.

Data-Driven Prediction for Industrial Processes and Their Applications

Author : Jun Zhao
Publisher : Springer
ISBN 13 : 3319940511
Total Pages : 443 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Data-Driven Prediction for Industrial Processes and Their Applications by : Jun Zhao

Download or read book Data-Driven Prediction for Industrial Processes and Their Applications written by Jun Zhao and published by Springer. This book was released on 2018-08-20 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.