Spatial Data Mining : Theory and Application
Language: English
Published by Springer Vieweg, 2018
- Softcover
- New

Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - This book is an updated version of awell-received book previously published in Chinese by Science Press of China(the first edition in 2006 and the second in 2013). It offers a systematic andpractical overview of spatial data mining, which combines computer science andgeo-spatial information science, allowing each field to profit from theknowledge and techniques of the other. To address the spatiotemporalspecialties of spatial data, the authors introduce the key concepts andalgorithms of the data field, cloud model, mining view, and Deren Li methods.The data field method captures the interactions between spatial objects bydiffusing the data contribution from a universe of samples to a universe ofpopulation, thereby bridging the gap between the data model and the recognitionmodel. The cloud model is a qualitative method that utilizes quantitativenumerical characters to bridge the gap between pure data and linguisticconcepts. The mining view method discriminates the different requirements byusing scale, hierarchy, and granularity in order to uncover the anisotropy ofspatial data mining. The Deren Li method performs data preprocessing to prepareit for further knowledge discovery by selecting a weight for iteration in orderto clean the observed spatial data as much as possible. In addition to theessential algorithms and techniques, the book provides application examples ofspatial data mining in geographic information science and remote sensing. Thepractical projects include spatiotemporal video data mining for protectingpublic security, serial image mining on nighttime lights for assessing theseverity of the Syrian Crisis, and the applications in the government project'the Belt and Road Initiatives'.…
Seller Inventory # 9783662569368
- Title
- Spatial Data Mining : Theory and Application
- Author
- Deren Li
- Publisher
- Springer Vieweg
- Publication year
- 2018
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3662569361
- ISBN 13
- 9783662569368
- Item weight
- 511 grams
- Dimensions
- 235x155x19 mm
· This book is an updated version of a well-received book previously published in Chinese by Science Press of China (the first edition in 2006 and the second in 2013). It offers a systematic and practical overview of spatial data mining, which combines computer science and geo-spatial information science, allowing each field to profit from the knowledge and techniques of the other. To address the spatiotemporal specialties of spatial data, the authors introduce the key concepts and algorithms of the data field, cloud model, mining view, and Deren Li methods. The data field method captures the interactions between spatial objects by diffusing the data contribution from a universe of samples to a universe of population, thereby bridging the gap between the data model and the recognition model. The cloud model is a qualitative method that utilizes quantitative numerical characters to bridge the gap between pure data and linguistic concepts. The mining view method discriminates the different requirements by using scale, hierarchy, and granularity in order to uncover the anisotropy of spatial data mining. The Deren Li method performs data preprocessing to prepare it for further knowledge discovery by selecting a weight for iteration in order to clean the observed spatial data as much as possible. In addition to the essential algorithms and techniques, the book provides application examples of spatial data mining in geographic information science and remote sensing. The practical projects include spatiotemporal video data mining for protecting public security, serial image mining on nighttime lights for assessing the severity of the Syrian Crisis, and the applications in the government project ‘the Belt and Road Initiatives’.
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About the Author
Shuliang Wang, PhD, a scientist in data science and software engineering, is a professor in Beijing Institute of Technology in China. His research interests include spatial data mining, and software engineering. For his innovatory study of spatial data mining, he was awarded the Fifth Annual InfoSci-Journals Excellence in Research Awards of IGI Global, IEEE Outstanding Contribution Award for Granular Computing, and one of China’s National Excellent Doctoral Thesis Prizes.
Deyi Li, PhD, a scientist in computer science and artificial intelligence, is the founder of cloud model. He is now a professor in Tsinghua University in China, a membership of Chinese Academy of Engineering and a membership of the Euro-Asia International Academy of Science. His research interests include networked data mining, artificial intelligence with uncertainty, cloud computing, and cognitive physics. For his contribution, he was awarded many international and national prizes or awards, e.g. the Premium Award by IEE Headquarters, the IFAC World Congress Outstanding Paper Award, National Science and Technology Progress Award and so on.
"About the title" may belong to another edition of this title.
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