000 03443nam a22005055i 4500
001 978-3-662-48538-5
003 DE-He213
005 20200421111705.0
007 cr nn 008mamaa
008 160323s2015 gw | s |||| 0|eng d
020 _a9783662485385
_9978-3-662-48538-5
024 7 _a10.1007/978-3-662-48538-5
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
_2bisacsh
082 0 4 _a006.312
_223
100 1 _aLi, Deren.
_eauthor.
245 1 0 _aSpatial Data Mining
_h[electronic resource] :
_bTheory and Application /
_cby Deren Li, Shuliang Wang, Deyi Li.
250 _a1st ed. 2015.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2015.
300 _aXXVIII, 308 p. 103 illus., 81 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
520 _a� 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'. p>.
650 0 _aComputer science.
650 0 _aData mining.
650 0 _aArtificial intelligence.
650 0 _aRemote sensing.
650 1 4 _aComputer Science.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aRemote Sensing/Photogrammetry.
650 2 4 _aArtificial Intelligence (incl. Robotics).
700 1 _aWang, Shuliang.
_eauthor.
700 1 _aLi, Deyi.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783662485361
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-662-48538-5
912 _aZDB-2-SCS
942 _cEBK
999 _c55230
_d55230