TY - GEN
T1 - Big spatial data mining
AU - Wang, Shuliang
AU - Ding, Gangyi
AU - Zhong, Ming
PY - 2013
Y1 - 2013
N2 - In this paper, spatial data mining is discussed in the context of big data. Firstly, we elaborate the fact that spatial data plays a primary role in big data, attracting academic community, business industry and governments. Secondly, the adverse of spatial data mining is discussed, such as much garbage, heavy pollution and its difficulties in utilization. Finally, we dissect the value in spatial big data, expound the techniques to discover knowledge from spatial big data, and investigate the transformation from knowledge into data intelligences.
AB - In this paper, spatial data mining is discussed in the context of big data. Firstly, we elaborate the fact that spatial data plays a primary role in big data, attracting academic community, business industry and governments. Secondly, the adverse of spatial data mining is discussed, such as much garbage, heavy pollution and its difficulties in utilization. Finally, we dissect the value in spatial big data, expound the techniques to discover knowledge from spatial big data, and investigate the transformation from knowledge into data intelligences.
KW - Big data
KW - Data intelligence
KW - Spatial data mining
UR - https://www.scopus.com/pages/publications/84893317276
U2 - 10.1109/BigData.2013.6691764
DO - 10.1109/BigData.2013.6691764
M3 - Conference contribution
AN - SCOPUS:84893317276
SN - 9781479912926
T3 - Proceedings - 2013 IEEE International Conference on Big Data, Big Data 2013
SP - 13
EP - 21
BT - Proceedings - 2013 IEEE International Conference on Big Data, Big Data 2013
PB - IEEE Computer Society
T2 - 2013 IEEE International Conference on Big Data, Big Data 2013
Y2 - 6 October 2013 through 9 October 2013
ER -