Bisociative Knowledge Discovery
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Bisociative Knowledge Discovery
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Author : Michael R. Berthold
language : en
Publisher: Springer
Release Date : 2012-06-27
Bisociative Knowledge Discovery written by Michael R. Berthold and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-27 with Computers categories.
Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied to originates from one domain. The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of finding well defined global or local patterns they wanted to find domain bridging associations which are, by definition, not well defined since they will be especially interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art volume together with a detailed introduction to the book are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.
Bisociative Knowledge Discovery
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Author : Michael R. Berthold
language : en
Publisher: Springer
Release Date : 2012-07-05
Bisociative Knowledge Discovery written by Michael R. Berthold and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-05 with Computers categories.
Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied to originates from one domain. The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of finding well defined global or local patterns they wanted to find domain bridging associations which are, by definition, not well defined since they will be especially interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art volume together with a detailed introduction to the book are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.
Human Computer Interaction And Knowledge Discovery In Complex Unstructured Big Data
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2013-06-26
Human Computer Interaction And Knowledge Discovery In Complex Unstructured Big Data written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-26 with Computers categories.
This book constitutes the refereed proceedings of the Third Workshop on Human-Computer Interaction and Knowledge Discovery, HCI-KDD 2013, held in Maribor, Slovenia, in July 2013, at SouthCHI 2013. The 20 revised papers presented were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections on human-computer interaction and knowledge discovery, knowledge discovery and smart homes, smart learning environments, and visualization data analytics.
Machine Learning And Knowledge Discovery In Databases Part Ii
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Author : Dimitrios Gunopulos
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-06
Machine Learning And Knowledge Discovery In Databases Part Ii written by Dimitrios Gunopulos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-06 with Computers categories.
This three-volume set LNAI 6911, LNAI 6912, and LNAI 6913 constitutes the refereed proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases: ECML PKDD 2011, held in Athens, Greece, in September 2011. The 121 revised full papers presented together with 10 invited talks and 11 demos in the three volumes, were carefully reviewed and selected from about 600 paper submissions. The papers address all areas related to machine learning and knowledge discovery in databases as well as other innovative application domains such as supervised and unsupervised learning with some innovative contributions in fundamental issues; dimensionality reduction, distance and similarity learning, model learning and matrix/tensor analysis; graph mining, graphical models, hidden markov models, kernel methods, active and ensemble learning, semi-supervised and transductive learning, mining sparse representations, model learning, inductive logic programming, and statistical learning. a significant part of the papers covers novel and timely applications of data mining and machine learning in industrial domains.
Advances In Intelligent Data Analysis X
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Author : João Gama
language : en
Publisher: Springer
Release Date : 2011-10-25
Advances In Intelligent Data Analysis X written by João Gama and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-25 with Computers categories.
This book constitutes the refereed proceedings of the 10th International Conference on Intelligent Data Analysis, IDA 2011, held in Porto, Portugal, in October 2011. The 19 revised full papers and 16 revised poster papers resented together with 3 invited papers were carefully reviewed and selected from 73 submissions. All current aspects of intelligent data analysis are addressed, particularly intelligent support for modeling and analyzing complex, dynamical systems. The papers offer intelligent support for understanding evolving scientific and social systems including data collection and acquisition, such as crowd sourcing; data cleaning, semantics and markup; searching for data and assembling datasets from multiple sources; data processing, including workflows, mixed-initiative data analysis, and planning; data and information fusion; incremental, mixed-initiative model development, testing and revision; and visualization and dissemination of results; etc.
Machine Learning For Health Informatics
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Author : Andreas Holzinger
language : en
Publisher: Springer
Release Date : 2016-12-09
Machine Learning For Health Informatics written by Andreas Holzinger and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-09 with Computers categories.
Machine learning (ML) is the fastest growing field in computer science, and Health Informatics (HI) is amongst the greatest application challenges, providing future benefits in improved medical diagnoses, disease analyses, and pharmaceutical development. However, successful ML for HI needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science to visualization. Tackling complex challenges needs both disciplinary excellence and cross-disciplinary networking without any boundaries. Following the HCI-KDD approach, in combining the best of two worlds, it is aimed to support human intelligence with machine intelligence. This state-of-the-art survey is an output of the international HCI-KDD expert network and features 22 carefully selected and peer-reviewed chapters on hot topics in machine learning for health informatics; they discuss open problems and future challenges in order to stimulate further research and international progress in this field.
Computational Creativity
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Author : Tony Veale
language : en
Publisher: Springer
Release Date : 2019-07-25
Computational Creativity written by Tony Veale and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-25 with Computers categories.
Computational creativity is an emerging field of research within AI that focuses on the capacity of machines to both generate and evaluate novel outputs that would, if produced by a human, be considered creative. This book is intended to be a canonical text for this new discipline, through which researchers and students can absorb the philosophy of the field and learn its methods. After a comprehensive introduction to the idea of systematizing creativity the contributions address topics such as autonomous intentionality, conceptual blending, literature mining, computational design, models of novelty, evaluating progress in related research, computer-supported human creativity and human-supported computer creativity, common-sense knowledge, and models of social creativity. Products of this research will have real consequences for the worlds of entertainment, culture, science, education, design, and art, in addition to artificial intelligence, and the book will be of value to practitioners and students in all these domains.
Trends And Applications In Knowledge Discovery And Data Mining
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Author : Wei Lu
language : en
Publisher: Springer Nature
Release Date : 2020-10-14
Trends And Applications In Knowledge Discovery And Data Mining written by Wei Lu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-14 with Computers categories.
This book constitutes the thoroughly refereed post-workshop proceedings of the workshops that were held in conjunction with the 24th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2020, in Singapore, Singapore, in May 2020. The 17 revised full papers presented were carefully reviewed and selected from a total of 50 submissions. The five workshops were as follows: · First International Workshop on Literature-Based Discovery (LBD 2020) · Workshop on Data Science for Fake News (DSFN 2020) · Learning Data Representation for Clustering (LDRC 2020) · Ninth Workshop on Biologically Inspired Techniques for Data Mining (BDM · 2020) · First Pacific Asia Workshop on Game Intelligence & Informatics (GII 2020)
Knowledge Discovery And Measures Of Interest
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Author : Robert J. Hilderman
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-14
Knowledge Discovery And Measures Of Interest written by Robert J. Hilderman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-14 with Computers categories.
Knowledge Discovery and Measures of Interest is a reference book for knowledge discovery researchers, practitioners, and students. The knowledge discovery researcher will find that the material provides a theoretical foundation for measures of interest in data mining applications where diversity measures are used to rank summaries generated from databases. The knowledge discovery practitioner will find solid empirical evidence on which to base decisions regarding the choice of measures in data mining applications. The knowledge discovery student in a senior undergraduate or graduate course in databases and data mining will find the book is a good introduction to the concepts and techniques of measures of interest. In Knowledge Discovery and Measures of Interest, we study two closely related steps in any knowledge discovery system: the generation of discovered knowledge; and the interpretation and evaluation of discovered knowledge. In the generation step, we study data summarization, where a single dataset can be generalized in many different ways and to many different levels of granularity according to domain generalization graphs. In the interpretation and evaluation step, we study diversity measures as heuristics for ranking the interestingness of the summaries generated. The objective of this work is to introduce and evaluate a technique for ranking the interestingness of discovered patterns in data. It consists of four primary goals: To introduce domain generalization graphs for describing and guiding the generation of summaries from databases. To introduce and evaluate serial and parallel algorithms that traverse the domain generalization space described by the domain generalization graphs. To introduce and evaluate diversity measures as heuristic measures of interestingness for ranking summaries generated from databases. To develop the preliminary foundation for a theory of interestingness within the context of ranking summaries generated from databases. Knowledge Discovery and Measures of Interest is suitable as a secondary text in a graduate level course and as a reference for researchers and practitioners in industry.
Advances In Intelligent Data Analysis Xii
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Author : Allan Tucker
language : en
Publisher: Springer
Release Date : 2013-10-16
Advances In Intelligent Data Analysis Xii written by Allan Tucker and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-10-16 with Computers categories.
This book constitutes the refereed conference proceedings of the 12th International Conference on Intelligent Data Analysis, which was held in October 2013 in London, UK. The 36 revised full papers together with 3 invited papers were carefully reviewed and selected from 84 submissions handling all kinds of modeling and analysis methods, irrespective of discipline. The papers cover all aspects of intelligent data analysis, including papers on intelligent support for modeling and analyzing data from complex, dynamical systems.