Proceedings of the Seventh SIAM International Conference on Data Mining
Proceedings of the Seventh SIAM International Conference on Data Mining

Author: Chid Apte

Publisher: Proceedings in Applied Mathema

Published: 2007

Total Pages: 674

ISBN-13:

DOWNLOAD EBOOK

The Seventh SIAM International Conference on Data Mining (SDM 2007) continues a series of conferences whose focus is the theory and application of data mining to complex datasets in science, engineering, biomedicine, and the social sciences. These datasets challenge our abilities to analyze them because they are large and often noisy. Sophisticated, highperformance, and principled analysis techniques and algorithms, based on sound statistical foundations, are required. Visualization is often critically important; tuning for performance is a significant challenge; and the appropriate levels of abstraction to allow end-users to exploit sophisticated techniques and understand clearly both the constraints and interpretation of results are still something of an open question.

Proceedings of the Third SIAM International Conference on Data Mining
Proceedings of the Third SIAM International Conference on Data Mining

Author: Daniel Barbara

Publisher: SIAM

Published: 2003-01-01

Total Pages: 368

ISBN-13: 9780898715453

DOWNLOAD EBOOK

The third SIAM International Conference on Data Mining provided an open forum for the presentation, discussion and development of innovative algorithms, software and theories for data mining applications and data intensive computation. This volume includes 21 research papers.

Proceedings of the Sixth SIAM International Conference on Data Mining
Proceedings of the Sixth SIAM International Conference on Data Mining

Author: Joydeep Ghosh

Publisher: SIAM

Published: 2006-04-01

Total Pages: 662

ISBN-13: 9780898716115

DOWNLOAD EBOOK

The Sixth SIAM International Conference on Data Mining continues the tradition of presenting approaches, tools, and systems for data mining in fields such as science, engineering, industrial processes, healthcare, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high-performance, and principled analysis techniques and algorithms, based on sound statistical foundations. These techniques in turn require powerful visualization technologies; implementations that must be carefully tuned for performance; software systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them.

Proceedings of the Fifth SIAM International Conference on Data Mining
Proceedings of the Fifth SIAM International Conference on Data Mining

Author: Hillol Kargupta

Publisher: SIAM

Published: 2005-04-01

Total Pages: 670

ISBN-13: 9780898715934

DOWNLOAD EBOOK

The Fifth SIAM International Conference on Data Mining continues the tradition of providing an open forum for the presentation and discussion of innovative algorithms as well as novel applications of data mining. Advances in information technology and data collection methods have led to the availability of large data sets in commercial enterprises and in a wide variety of scientific and engineering disciplines. The field of data mining draws upon extensive work in areas such as statistics, machine learning, pattern recognition, databases, and high performance computing to discover interesting and previously unknown information in data. This conference results in data mining, including applications, algorithms, software, and systems.

Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015
Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Author: Robert Burduk

Publisher: Springer

Published: 2016-03-05

Total Pages: 827

ISBN-13: 3319262270

DOWNLOAD EBOOK

The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 79 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning, and classifiers Biometrics Data Stream Classification and Big Data Analytics Image processing and computer vision Medical applications Applications RGB-D perception: recent developments and applications This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

Graph Mining
Graph Mining

Author: Deepayan Chakrabarti

Publisher: Morgan & Claypool Publishers

Published: 2012-10-01

Total Pages: 209

ISBN-13: 160845116X

DOWNLOAD EBOOK

What does the Web look like? How can we find patterns, communities, outliers, in a social network? Which are the most central nodes in a network? These are the questions that motivate this work. Networks and graphs appear in many diverse settings, for example in social networks, computer-communication networks (intrusion detection, traffic management), protein-protein interaction networks in biology, document-text bipartite graphs in text retrieval, person-account graphs in financial fraud detection, and others. In this work, first we list several surprising patterns that real graphs tend to follow. Then we give a detailed list of generators that try to mirror these patterns. Generators are important, because they can help with "what if" scenarios, extrapolations, and anonymization. Then we provide a list of powerful tools for graph analysis, and specifically spectral methods (Singular Value Decomposition (SVD)), tensors, and case studies like the famous "pageRank" algorithm and the "HITS" algorithm for ranking web search results. Finally, we conclude with a survey of tools and observations from related fields like sociology, which provide complementary viewpoints. Table of Contents: Introduction / Patterns in Static Graphs / Patterns in Evolving Graphs / Patterns in Weighted Graphs / Discussion: The Structure of Specific Graphs / Discussion: Power Laws and Deviations / Summary of Patterns / Graph Generators / Preferential Attachment and Variants / Incorporating Geographical Information / The RMat / Graph Generation by Kronecker Multiplication / Summary and Practitioner's Guide / SVD, Random Walks, and Tensors / Tensors / Community Detection / Influence/Virus Propagation and Immunization / Case Studies / Social Networks / Other Related Work / Conclusions

Social Network Based Big Data Analysis and Applications
Social Network Based Big Data Analysis and Applications

Author: Mehmet Kaya

Publisher: Springer

Published: 2018-05-10

Total Pages: 254

ISBN-13: 3319781960

DOWNLOAD EBOOK

This book is a timely collection of chapters that present the state of the art within the analysis and application of big data. Working within the broader context of big data, this text focuses on the hot topics of social network modelling and analysis such as online dating recommendations, hiring practices, and subscription-type prediction in mobile phone services. Manuscripts are expanded versions of the best papers presented at the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM’2016), which was held in August 2016. The papers were among the best featured at the meeting and were then improved and extended substantially. Social Network Based Big Data Analysis and Applications will appeal to students and researchers in the field.

Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications
Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications

Author: Marie-Jeanne Lesot

Publisher: Springer Nature

Published: 2020-10-26

Total Pages: 305

ISBN-13: 3030543412

DOWNLOAD EBOOK

This book gathers cutting-edge papers in the area of Computational Intelligence, presented by specialists, and covering all major trends in the research community in order to provide readers with a rich primer. It presents an overview of various soft computing topics and approximate reasoning-based approaches, both from theoretical and applied perspectives. Numerous topics are covered: fundamentals aspects of fuzzy sets theory, reasoning approaches (interpolative, analogical, similarity-based), decision and optimization theory, fuzzy databases, soft machine learning, summarization, interpretability and XAI. Moreover, several application-based papers are included, e.g. on image processing, semantic web and intelligent tutoring systems. This book is dedicated to Bernadette Bouchon-Meunier in honor of her achievements in Computational Intelligence, which, throughout her career, have included profuse and diverse collaborations, both thematically and geographically.