Spatial data mining : theory and application / Deren Li, Shuliang Wang and Deyi Li.
Material type:
TextPublication details: Berlin : Springer-Verlag, 2015.Description: xxviii, 308 pages : illustrations (some color) ; 24 cmISBN: - 9783662485361
- 006.312 23 L693
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 006.312 L693 (Browse shelf(Opens below)) | Available | 137470 |
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| 006.312 L474 Data mining and business analytics with R / | 006.312 L474 Data mining and business analytics with R / | 006.312 L478 Fundamentals of big data network analysis for research and industry / | 006.312 L693 Spatial data mining : | 006.312 M664 Practical text mining and statistical analysis for non-structured text data applications | 006.312 M675 Clustering : a data recovery approach / | 006.312 M678 On some estimation problems through the sub-linear lens/ |
Includes bibliographical references.
1. Introduction.-
2. SDM principles.-
3. SDM Data source.-
4. Spatial Data Cleaning.-
5. Methods and Techniques in SDM.-
6. Data field.-
7. Cloud Model.-
8. GIS Data Mining.-
9. Remote Sensing Image Mining.-
10. SDM system.
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.
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