Information Fusion In Data Mining
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| Author | : Prof. Vicenç Torra |
| Publisher | : Springer |
| Total Pages | : 232 |
| Release | : 2013-06-05 |
| Genre | : Technology & Engineering |
| ISBN | : 3540365192 |
Information fusion is becoming a major requirement in data mining and knowledge discovery in databases. This book presents some recent fusion techniques that are currently in use in data mining, as well as data mining applications that use information fusion. Special focus of the book is on information fusion in preprocessing, model building and information extraction with various applications.
| Author | : National Research Council |
| Publisher | : National Academies Press |
| Total Pages | : 377 |
| Release | : 2008-10-26 |
| Genre | : Computers |
| ISBN | : 0309124883 |
All U.S. agencies with counterterrorism programs that collect or "mine" personal data-such as phone records or Web sites visited-should be required to evaluate the programs' effectiveness, lawfulness, and impacts on privacy. A framework is offered that agencies can use to evaluate such information-based programs, both classified and unclassified. The book urges Congress to re-examine existing privacy law to assess how privacy can be protected in current and future programs and recommends that any individuals harmed by violations of privacy be given a meaningful form of redress. Two specific technologies are examined: data mining and behavioral surveillance. Regarding data mining, the book concludes that although these methods have been useful in the private sector for spotting consumer fraud, they are less helpful for counterterrorism because so little is known about what patterns indicate terrorist activity. Regarding behavioral surveillance in a counterterrorist context, the book concludes that although research and development on certain aspects of this topic are warranted, there is no scientific consensus on whether these techniques are ready for operational use at all in counterterrorism.
| Author | : Xanthoula Eirini Pantazi |
| Publisher | : Academic Press |
| Total Pages | : 330 |
| Release | : 2019-10-08 |
| Genre | : Business & Economics |
| ISBN | : 0128143924 |
Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms. Covers crop protection, automation in agriculture, artificial intelligence in agriculture, sensing and Internet of Things (IoTs) in agriculture Addresses AI use in weed management, disease detection, yield prediction and crop production Utilizes case studies to provide real-world insights and direction
| Author | : Vicenç Torra |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 284 |
| Release | : 2007-05-11 |
| Genre | : Computers |
| ISBN | : 3540687912 |
This book covers the underlying science and application issues related to aggregation operators, focusing on tools used in practical applications that involve numerical information. It will thus be required reading for engineers, statisticians and computer scientists of all kinds. Starting with detailed introductions to information fusion and integration, measurement and probability theory, fuzzy sets, and functional equations, the authors then cover numerous topics in detail, including the synthesis of judgements, fuzzy measures, weighted means and fuzzy integrals.
| Author | : Martin Liggins II |
| Publisher | : CRC Press |
| Total Pages | : 872 |
| Release | : 2017-01-06 |
| Genre | : Technology & Engineering |
| ISBN | : 1420053094 |
In the years since the bestselling first edition, fusion research and applications have adapted to service-oriented architectures and pushed the boundaries of situational modeling in human behavior, expanding into fields such as chemical and biological sensing, crisis management, and intelligent buildings. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition represents the most current concepts and theory as information fusion expands into the realm of network-centric architectures. It reflects new developments in distributed and detection fusion, situation and impact awareness in complex applications, and human cognitive concepts. With contributions from the world’s leading fusion experts, this second edition expands to 31 chapters covering the fundamental theory and cutting-edge developments that are driving this field. New to the Second Edition— · Applications in electromagnetic systems and chemical and biological sensors · Army command and combat identification techniques · Techniques for automated reasoning · Advances in Kalman filtering · Fusion in a network centric environment · Service-oriented architecture concepts · Intelligent agents for improved decision making · Commercial off-the-shelf (COTS) software tools From basic information to state-of-the-art theories, this second edition continues to be a unique, comprehensive, and up-to-date resource for data fusion systems designers.
| Author | : David Hall |
| Publisher | : CRC Press |
| Total Pages | : 564 |
| Release | : 2001-06-20 |
| Genre | : Technology & Engineering |
| ISBN | : 1420038540 |
The emerging technology of multisensor data fusion has a wide range of applications, both in Department of Defense (DoD) areas and in the civilian arena. The techniques of multisensor data fusion draw from an equally broad range of disciplines, including artificial intelligence, pattern recognition, and statistical estimation. With the rapid evolut
| Author | : Shi Yu |
| Publisher | : Springer |
| Total Pages | : 223 |
| Release | : 2011-03-29 |
| Genre | : Technology & Engineering |
| ISBN | : 3642194060 |
Data fusion problems arise frequently in many different fields. This book provides a specific introduction to data fusion problems using support vector machines. In the first part, this book begins with a brief survey of additive models and Rayleigh quotient objectives in machine learning, and then introduces kernel fusion as the additive expansion of support vector machines in the dual problem. The second part presents several novel kernel fusion algorithms and some real applications in supervised and unsupervised learning. The last part of the book substantiates the value of the proposed theories and algorithms in MerKator, an open software to identify disease relevant genes based on the integration of heterogeneous genomic data sources in multiple species. The topics presented in this book are meant for researchers or students who use support vector machines. Several topics addressed in the book may also be interesting to computational biologists who want to tackle data fusion challenges in real applications. The background required of the reader is a good knowledge of data mining, machine learning and linear algebra.
| Author | : Marina Cocchi |
| Publisher | : Elsevier |
| Total Pages | : 396 |
| Release | : 2019-05-11 |
| Genre | : Science |
| ISBN | : 0444639853 |
Data Fusion Methodology and Applications explores the data-driven discovery paradigm in science and the need to handle large amounts of diverse data. Drivers of this change include the increased availability and accessibility of hyphenated analytical platforms, imaging techniques, the explosion of omics data, and the development of information technology. As data-driven research deals with an inductive attitude that aims to extract information and build models capable of inferring the underlying phenomena from the data itself, this book explores the challenges and methodologies used to integrate data from multiple sources, analytical platforms, different modalities, and varying timescales. Presents the first comprehensive textbook on data fusion, focusing on all aspects of data-driven discovery Includes comprehensible, theoretical chapters written for large and diverse audiences Provides a wealth of selected application to the topics included
| Author | : Éloi Bossé |
| Publisher | : Springer |
| Total Pages | : 620 |
| Release | : 2019-04-02 |
| Genre | : Computers |
| ISBN | : 303003643X |
This book presents a contemporary view of the role of information quality in information fusion and decision making, and provides a formal foundation and the implementation strategies required for dealing with insufficient information quality in building fusion systems for decision making. Information fusion is the process of gathering, processing, and combining large amounts of information from multiple and diverse sources, including physical sensors to human intelligence reports and social media. That data and information may be unreliable, of low fidelity, insufficient resolution, contradictory, fake and/or redundant. Sources may provide unverified reports obtained from other sources resulting in correlations and biases. The success of the fusion processing depends on how well knowledge produced by the processing chain represents reality, which in turn depends on how adequate data are, how good and adequate are the models used, and how accurate, appropriate or applicable prior and contextual knowledge is. By offering contributions by leading experts, this book provides an unparalleled understanding of the problem of information quality in information fusion and decision-making for researchers and professionals in the field.
| Author | : |
| Publisher | : |
| Total Pages | : 14 |
| Release | : 1999 |
| Genre | : |
| ISBN | : |
The recent developments in the definition of doctrine for information operations and the implementation of systems to enable the conduct of those operations pose new challenges to the application of data fusion and data mining technologies. This paper describes the basic reasoning processes underlying both data fusion and data mining, and discusses the critical role of these processes to enable the development of increasingly complex information operations (IO). The development of IO, this paper asserts, has opened three challenging frontiers of development that must be addressed by data fusion and mining developers. These frontiers include: (1) The need to apply the processes beyond the physical domain, to encompass the symbolic and cognitive domains of reality, (2) The need to extend the processes to deal with subjective and qualitative data, and (3) The need to develop collaborative fusion and mining processes that collaborate with human teams to solve complex problems.
