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Knowledge Discovery From Sensor Data

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Knowledge Discovery From Sensor Data

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Author : Auroop R. Ganguly
language : en
Publisher: CRC Press
Release Date : 2008-12-10

Knowledge Discovery From Sensor Data written by Auroop R. Ganguly and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-10 with Business & Economics categories.

As sensors become ubiquitous, a set of broad requirements is beginning to emerge across high-priority applications including disaster preparedness and management, adaptability to climate change, national or homeland security, and the management of critical infrastructures. This book presents innovative solutions in offline data mining and real-time

Knowledge Discovery From Sensor Data

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Author : Mohamed Medhat Gaber
language : en
Publisher: Springer
Release Date : 2010-04-07

Knowledge Discovery From Sensor Data written by Mohamed Medhat Gaber and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-04-07 with Computers categories.

This book contains thoroughly refereed extended papers from the Second International Workshop on Knowledge Discovery from Sensor Data, Sensor-KDD 2008, held in Las Vegas, NV, USA, in August 2008. The 12 revised papers presented together with an invited paper were carefully reviewed and selected from numerous submissions. The papers feature important aspects of knowledge discovery from sensor data, e.g., data mining for diagnostic debugging; incremental histogram distribution for change detection; situation-aware adaptive visualization; WiFi mining; mobile sensor data mining; incremental anomaly detection; and spatiotemporal neighborhood discovery for sensor data.

Knowledge Discovery From Sensor Data

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Author : Mohamed Medhat Gaber
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-04-14

Knowledge Discovery From Sensor Data written by Mohamed Medhat Gaber 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 2010-04-14 with Computers categories.

Knowledge Discovery From Sensor Data

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Author : Mohamed Medhat Gaber
language : en
Publisher: Springer
Release Date : 2010-04-23

Urban Informatics

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Author : Wenzhong Shi
language : en
Publisher: Springer Nature
Release Date : 2021-04-06

Urban Informatics written by Wenzhong Shi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-06 with Social Science categories.

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.

Managing And Mining Sensor Data

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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-15

Managing And Mining Sensor Data written by Charu C. Aggarwal 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 2013-01-15 with Computers categories.

Advances in hardware technology have lead to an ability to collect data with the use of a variety of sensor technologies. In particular sensor notes have become cheaper and more efficient, and have even been integrated into day-to-day devices of use, such as mobile phones. This has lead to a much larger scale of applicability and mining of sensor data sets. The human-centric aspect of sensor data has created tremendous opportunities in integrating social aspects of sensor data collection into the mining process. Managing and Mining Sensor Data is a contributed volume by prominent leaders in this field, targeting advanced-level students in computer science as a secondary text book or reference. Practitioners and researchers working in this field will also find this book useful.

Learning From Data Streams

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Author : João Gama
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-20

Learning From Data Streams written by João Gama 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 2007-09-20 with Computers categories.

Sensor networks consist of distributed autonomous devices that cooperatively monitor an environment. Sensors are equipped with capacities to store information in memory, process this information and communicate with their neighbors. Processing data streams generated from wireless sensor networks has raised new research challenges over the last few years due to the huge numbers of data streams to be managed continuously and at a very high rate. The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education. This research monograph delivers to researchers and graduate students the state of the art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research.

Knowledge Discovery From Data Streams

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Author : Joao Gama
language : en
Publisher: CRC Press
Release Date : 2010-05-25

Knowledge Discovery From Data Streams written by Joao Gama and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-25 with Business & Economics categories.

Since the beginning of the Internet age and the increased use of ubiquitous computing devices, the large volume and continuous flow of distributed data have imposed new constraints on the design of learning algorithms. Exploring how to extract knowledge structures from evolving and time-changing data, Knowledge Discovery from Data Streams presents a coherent overview of state-of-the-art research in learning from data streams. The book covers the fundamentals that are imperative to understanding data streams and describes important applications, such as TCP/IP traffic, GPS data, sensor networks, and customer click streams. It also addresses several challenges of data mining in the future, when stream mining will be at the core of many applications. These challenges involve designing useful and efficient data mining solutions applicable to real-world problems. In the appendix, the author includes examples of publicly available software and online data sets. This practical, up-to-date book focuses on the new requirements of the next generation of data mining. Although the concepts presented in the text are mainly about data streams, they also are valid for different areas of machine learning and data mining.

Proceedings Of The Third International Workshop On Knowledge Discovery From Sensor Data

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Author : Association for Computing Machinery. Special Interest Group on Knowledge Discovery & Data Mining
language : en
Publisher:
Release Date : 2009-06-28

Proceedings Of The Third International Workshop On Knowledge Discovery From Sensor Data written by Association for Computing Machinery. Special Interest Group on Knowledge Discovery & Data Mining and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-06-28 with Data mining categories.

KDD '09: The 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining Jun 28, 2009-Jul 01, 2009 Paris, France. You can view more information about this proceeding and all of ACMs other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.

Feature Selection For Knowledge Discovery And Data Mining

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Author : Huan Liu
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Feature Selection For Knowledge Discovery And Data Mining written by Huan Liu 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 2012-12-06 with Computers categories.

As computer power grows and data collection technologies advance, a plethora of data is generated in almost every field where computers are used. The com puter generated data should be analyzed by computers; without the aid of computing technologies, it is certain that huge amounts of data collected will not ever be examined, let alone be used to our advantages. Even with today's advanced computer technologies (e. g. , machine learning and data mining sys tems), discovering knowledge from data can still be fiendishly hard due to the characteristics of the computer generated data. Taking its simplest form, raw data are represented in feature-values. The size of a dataset can be measUJ·ed in two dimensions, number of features (N) and number of instances (P). Both Nand P can be enormously large. This enormity may cause serious problems to many data mining systems. Feature selection is one of the long existing methods that deal with these problems. Its objective is to select a minimal subset of features according to some reasonable criteria so that the original task can be achieved equally well, if not better. By choosing a minimal subset offeatures, irrelevant and redundant features are removed according to the criterion. When N is reduced, the data space shrinks and in a sense, the data set is now a better representative of the whole data population. If necessary, the reduction of N can also give rise to the reduction of P by eliminating duplicates.

Knowledge Discovery From Sensor Data

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