New Frontiers in Applied Data Mining
New Frontiers in Applied Data Mining

Author: Sanjay Chawla

Publisher: Springer Science & Business Media

Published: 2009-02-16

Total Pages: 226

ISBN-13: 3642003982

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This book constitutes the proceedings of the PAKDD Workshops 2008, namely ALSIP 2008, DMDRM 2008, and IDM 2008. The workshops were held in conjunction with the PAKDD conference in Osaka, Japan, during May 20-23, 2008. The 17 papers presented were carefully reviewed and selected from 38 submissions. The International Workshop on Algorithms for Large-Sale Information Processing in Knowledge Discovery (ALSIP) focused on exchanging fresh ideas on large-scale data processing in the problems of data mining, clustering, machine learning, statistical analysis, and other computational aspects of knowledge discovery problems. The Workshop on Data Mining for Decision Making and Risk Management (DMDRM) covered data mining and machine learning approaches, statistical approaches, chance discovery, active mining and application of these techniques to medicine, marketing, security, decision support in business, social activities, human relationships, chemistry and sensor data. The Workshop on Interactive Data Mining Overview (IDM) discussed various interactive data mining researches such as interactive information retrieval, information gathering sysetms, personalization systems, recommendation systems, user interfaces.

New Frontiers in Applied Data Mining
New Frontiers in Applied Data Mining

Author: Thanaruk Theeramunkong

Publisher: Springer Science & Business Media

Published: 2010-08-18

Total Pages: 181

ISBN-13: 3642146392

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This book constitutes the proceedings of the PAKDD 2009 International Workshops on New Frontiers in Applied Data Mining, held in Bangkok, Thailand in April 2010.

New Frontiers in Applied Data Mining
New Frontiers in Applied Data Mining

Author: Longbing Cao

Publisher: Springer Science & Business Media

Published: 2012-02-15

Total Pages: 526

ISBN-13: 3642283195

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This book constitutes the thoroughly refereed post-conference proceedings of five international workshops held in conjunction with PAKDD 2011 in Shenzhen, China, in May 2011: the International Workshop on Behavior Informatics (BI 2011), the Workshop on Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE 2011), the Workshop on Biologically Inspired Techniques for Data Mining (BDM 2011), the Workshop on Advances and Issues in Traditional Chinese Medicine Clinical Data Mining (AI-TCM 2011), and the Second Workshop on Data Mining for Healthcare Management (DMGHM 2011). The book also includes papers from the First PAKDD Doctoral Symposium on Data Mining (DSDM 2011). The 42 papers were carefully reviewed and selected from numerous submissions. The papers cover a wide range of topics discussing emerging techniques in the field of knowledge discovery in databases and their application domains extending to previously unexplored areas such as data mining based on optimization techniques from biological behavior of animals and applications in Traditional Chinese Medicine clinical research and health care management.

Computational Intelligence in Data Mining - Volume 2
Computational Intelligence in Data Mining - Volume 2

Author: Lakhmi C. Jain

Publisher: Springer

Published: 2014-12-10

Total Pages: 696

ISBN-13: 8132222083

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The contributed volume aims to explicate and address the difficulties and challenges that of seamless integration of the two core disciplines of computer science, i.e., computational intelligence and data mining. Data Mining aims at the automatic discovery of underlying non-trivial knowledge from datasets by applying intelligent analysis techniques. The interest in this research area has experienced a considerable growth in the last years due to two key factors: (a) knowledge hidden in organizations’ databases can be exploited to improve strategic and managerial decision-making; (b) the large volume of data managed by organizations makes it impossible to carry out a manual analysis. The book addresses different methods and techniques of integration for enhancing the overall goal of data mining. The book helps to disseminate the knowledge about some innovative, active research directions in the field of data mining, machine and computational intelligence, along with some current issues and applications of related topics.

Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection
Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection

Author: Koyuncugil, Ali Serhan

Publisher: IGI Global

Published: 2010-09-30

Total Pages: 355

ISBN-13: 1616928670

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Surveillance Technologies and Early Warning Systems: Data Mining Applications for Risk Detection has never been more important, as the research this book presents an alternative to conventional surveillance and risk assessment. This book is a multidisciplinary excursion comprised of data mining, early warning systems, information technologies and risk management and explores the intersection of these components in problematic domains. It offers the ability to apply the most modern techniques to age old problems allowing for increased effectiveness in the response to future, eminent, and present risk.

New Frontiers in Applied Artificial Intelligence
New Frontiers in Applied Artificial Intelligence

Author: Ngoc Thanh Nguyen

Publisher: Springer Science & Business Media

Published: 2008-06-03

Total Pages: 896

ISBN-13: 354069045X

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This book constitutes the refereed proceedings of the 21st International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2008, held in Wroclaw, Poland, in June 2008. The 75 revised full papers presented were carefully reviewed and selected from 302 submissions. The papers are organized in topical sections on computer vision, fuzzy system applications, robot and manufacturing, data mining and KDS, neural networks, machine learning, natural language processing, internet application and education, heuristic search, application systems, agent-based system, evolutionary and genetic algorithms, knowledge management, and other applications. The book concludes with 15 contributions from the following special sessions: knowledge driven manufacturing systems, joint session on adaptive networked systems and fuzzy knowledge bases, and software agents and multi-agent systems.

Mining of Data with Complex Structures
Mining of Data with Complex Structures

Author: Fedja Hadzic

Publisher: Springer Science & Business Media

Published: 2011-01-30

Total Pages: 340

ISBN-13: 3642175562

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Mining of Data with Complex Structures: - Clarifies the type and nature of data with complex structure including sequences, trees and graphs - Provides a detailed background of the state-of-the-art of sequence mining, tree mining and graph mining. - Defines the essential aspects of the tree mining problem: subtree types, support definitions, constraints. - Outlines the implementation issues one needs to consider when developing tree mining algorithms (enumeration strategies, data structures, etc.) - Details the Tree Model Guided (TMG) approach for tree mining and provides the mathematical model for the worst case estimate of complexity of mining ordered induced and embedded subtrees. - Explains the mechanism of the TMG framework for mining ordered/unordered induced/embedded and distance-constrained embedded subtrees. - Provides a detailed comparison of the different tree mining approaches highlighting the characteristics and benefits of each approach. - Overviews the implications and potential applications of tree mining in general knowledge management related tasks, and uses Web, health and bioinformatics related applications as case studies. - Details the extension of the TMG framework for sequence mining - Provides an overview of the future research direction with respect to technical extensions and application areas The primary audience is 3rd year, 4th year undergraduate students, Masters and PhD students and academics. The book can be used for both teaching and research. The secondary audiences are practitioners in industry, business, commerce, government and consortiums, alliances and partnerships to learn how to introduce and efficiently make use of the techniques for mining of data with complex structures into their applications. The scope of the book is both theoretical and practical and as such it will reach a broad market both within academia and industry. In addition, its subject matter is a rapidly emerging field that is critical for efficient analysis of knowledge stored in various domains.

Biologically-Inspired Techniques for Knowledge Discovery and Data Mining
Biologically-Inspired Techniques for Knowledge Discovery and Data Mining

Author: Alam, Shafiq

Publisher: IGI Global

Published: 2014-05-31

Total Pages: 397

ISBN-13: 1466660791

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Biologically-inspired data mining has a wide variety of applications in areas such as data clustering, classification, sequential pattern mining, and information extraction in healthcare and bioinformatics. Over the past decade, research materials in this area have dramatically increased, providing clear evidence of the popularity of these techniques. Biologically-Inspired Techniques for Knowledge Discovery and Data Mining exemplifies prestigious research and shares the practices that have allowed these areas to grow and flourish. This essential reference publication highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems. Providing quality work from established researchers, this publication serves to extend existing knowledge within the research communities of data mining and knowledge discovery, as well as for academicians and students in the field.

Emerging Methods in Predictive Analytics: Risk Management and Decision-Making
Emerging Methods in Predictive Analytics: Risk Management and Decision-Making

Author: Hsu, William H.

Publisher: IGI Global

Published: 2014-01-31

Total Pages: 447

ISBN-13: 1466650648

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Decision making tools are essential for the successful outcome of any organization. Recent advances in predictive analytics have aided in identifying particular points of leverage where critical decisions can be made. Emerging Methods in Predictive Analytics: Risk Management and Decision Making provides an interdisciplinary approach to predictive analytics; bringing together the fields of business, statistics, and information technology for effective decision making. Managers, business professionals, and decision makers in diverse fields will find the applications and cases presented in this text essential in providing new avenues for risk assessment, management, and predicting the future outcomes of their decisions.

Recent Advances on Soft Computing and Data Mining
Recent Advances on Soft Computing and Data Mining

Author: Tutut Herawan

Publisher: Springer

Published: 2014-05-29

Total Pages: 697

ISBN-13: 3319076922

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This book constitutes the refereed proceedings of the First International Conference on Soft Computing and Data Mining, SCDM 2014, held in Universiti Tun Hussein Onn Malaysia, in June 16th-18th, 2014. The 65 revised full papers presented in this book were carefully reviewed and selected from 145 submissions, and organized into two main topical sections; Data Mining and Soft Computing. The goal of this book is to provide both theoretical concepts and, especially, practical techniques on these exciting fields of soft computing and data mining, ready to be applied in real-world applications. The exchanges of views pertaining future research directions to be taken in this field and the resultant dissemination of the latest research findings makes this work of immense value to all those having an interest in the topics covered.