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Developing Multi-Database Mining Applications

Author: Animesh Adhikari

Publisher: Springer Science & Business Media

Published: 2010-06-14

Total Pages: 134

ISBN-13: 1849960445

Multi-database mining has been recognized recently as an important and strategically essential area of research in data mining. In this book, we discuss various issues regarding the systematic and efficient development of multi-database mining applications. It explains how systematically one could prepare data warehouses at different branches. As appropriate multi-database mining technique is essential to develop better applications. Also, the efficiency of a multi-database mining application could be improved by processing more patterns in the application. A faster algorithm could also play an important role in developing a better application. Thus the efficiency of a multi-database mining application could be enhanced by choosing an appropriate multi-database mining model, an appropriate pattern synthesizing technique, a better pattern representation technique, and an efficient algorithm for solving the problem. This book illustrates each of these issues either in the context of a specific problem, or in general.

Transactions on Computational Science XXXIV

Author: Marina L. Gavrilova

Publisher: Springer Nature

Published: 2019-08-28

Total Pages: 137

ISBN-13: 3662599589

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The LNCS journal Transactions on Computational Science reflects recent developments in the field of Computational Science, conceiving the field not as a mere ancillary science but rather as an innovative approach supporting many other scientific disciplines. The journal focuses on original high-quality research in the realm of computational science in parallel and distributed environments, encompassing the facilitating theoretical foundations and the applications of large-scale computations and massive data processing. It addresses researchers and practitioners in areas ranging from aerospace to biochemistry, from electronics to geosciences, from mathematics to software architecture, presenting verifiable computational methods, findings, and solutions, and enabling industrial users to apply techniques of leading-edge, large-scale, high performance computational methods. This, the 34th issue of the Transactions on Computational Science, contains seven in-depth papers focusing on research on data analytics using machine learning and pattern recognition, with applications in wireless networks, databases, and remotely sensed data.

Association Rule Mining

Author: Chengqi Zhang

Publisher: Springer

Published: 2003-08-01

Total Pages: 247

ISBN-13: 3540460276

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Due to the popularity of knowledge discovery and data mining, in practice as well as among academic and corporate R&D professionals, association rule mining is receiving increasing attention. The authors present the recent progress achieved in mining quantitative association rules, causal rules, exceptional rules, negative association rules, association rules in multi-databases, and association rules in small databases. This book is written for researchers, professionals, and students working in the fields of data mining, data analysis, machine learning, knowledge discovery in databases, and anyone who is interested in association rule mining.

Ethical Data Mining Applications for Socio-Economic Development

Author: Hakikur Rahman

Publisher: IGI Global

Published: 2013-05-31

Total Pages: 360

ISBN-13: 1466640790

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"This book provides an overview of data mining techniques under an ethical lens, investigating developments in research best practices and examining experimental cases to identify potential ethical dilemmas in the information and communications technology sector"--Provided by publisher.

Data Mining and Multi-agent Integration

Author: Longbing Cao

Publisher: Springer Science & Business Media

Published: 2009-07-25

Total Pages: 335

ISBN-13: 1441905227

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Data Mining and Multi agent Integration aims to re?ect state of the art research and development of agent mining interaction and integration (for short, agent min ing). The book was motivated by increasing interest and work in the agents data min ing, and vice versa. The interaction and integration comes about from the intrinsic challenges faced by agent technology and data mining respectively; for instance, multi agent systems face the problem of enhancing agent learning capability, and avoiding the uncertainty of self organization and intelligence emergence. Data min ing, if integrated into agent systems, can greatly enhance the learning skills of agents, and assist agents with predication of future states, thus initiating follow up action or intervention. The data mining community is now struggling with mining distributed, interactive and heterogeneous data sources. Agents can be used to man age such data sources for data access, monitoring, integration, and pattern merging from the infrastructure, gateway, message passing and pattern delivery perspectives. These two examples illustrate the potential of agent mining in handling challenges in respective communities. There is an excellent opportunity to create innovative, dual agent mining interac tion and integration technology, tools and systems which will deliver results in one new technology.

Database Design

Author: Michael Mannino

Publisher: SAGE Publications

Published: 2018-09-15

Total Pages: 872

ISBN-13: 1948426064

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Formerly published by Chicago Business Press, now published by Sage Database Design, Application Development, and Administration, Seventh Edition, offers a comprehensive understanding of database technology. Author Michael Mannino equips students with the necessary tools to grasp the fundamental concepts of database management, and then guides them in honing their skills to solve both basic and advanced challenges in query formulation, data modeling, and database application development.

Handbook of Statistical Analysis and Data Mining Applications

Author: Robert Nisbet

Publisher: Elsevier

Published: 2017-11-09

Total Pages: 822

ISBN-13: 0124166458

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Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

IT Roadmap to a Geospatial Future

Author: National Research Council

Publisher: National Academies Press

Published: 2003-05-04

Total Pages: 136

ISBN-13: 0309087384

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A grand challenge for science is to understand the human implications of global environmental change and to help society cope with those changes. Virtually all the scientific questions associated with this challenge depend on geospatial information (geoinformation) and on the ability of scientists, working individually and in groups, to interact with that information in flexible and increasingly complex ways. Another grand challenge is how to respond to calamities-terrorist activities, other human-induced crises, and natural disasters. Much of the information that underpins emergency preparedness, response, recovery, and mitigation is geospatial in nature. In terrorist situations, for example, origins and destinations of phone calls and e-mail messages, travel patterns of individuals, dispersal patterns of airborne chemicals, assessment of places at risk, and the allocation of resources all involve geospatial information. Much of the work addressing environment- and emergency-related concerns will depend on how productively humans are able to integrate, distill, and correlate a wide range of seemingly unrelated information. In addition to critical advances in location-aware computing, databases, and data mining methods, advances in the human-computer interface will couple new computational capabilities with human cognitive capabilities. This report outlines an interdisciplinary research roadmap at the intersection of computer science and geospatial information science. The report was developed by a committee convened by the Computer Science and Telecommunications Board of the National Research Council.

Autonomous Intelligent Systems: Agents and Data Mining

Author: Vladimir Gorodetsky

Publisher: Springer Science & Business Media

Published: 2005-05-30

Total Pages: 313

ISBN-13: 3540261648

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This book constitutes the refereed proceedings of the International Workshop on Autonomous Intelligent Systems: Agents and Data Mining, AIS-ADM 2005, held in St. Petersburg, Russia in June 2005. The 17 revised full papers presented together with 5 invited papers and the abstract of an invited talk were carefully reviewed and selected from 29 submissions. The papers are organized in topical sections on agent-based data mining issues, ontologies and Web mining, and applications and case studies.

Data Warehousing and Mining: Concepts, Methodologies, Tools, and Applications

Author: Wang, John

Publisher: IGI Global

Published: 2008-05-31

Total Pages: 4092

ISBN-13: 159904952X

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In recent years, the science of managing and analyzing large datasets has emerged as a critical area of research. In the race to answer vital questions and make knowledgeable decisions, impressive amounts of data are now being generated at a rapid pace, increasing the opportunities and challenges associated with the ability to effectively analyze this data.