TY - GEN
T1 - Complex spatial relationships
AU - Munro, Robert
AU - Chawla, Sanjay
AU - Sun, Pei
PY - 2003
Y1 - 2003
N2 - This paper describes the need for mining complex relationships in spatial data. Complex relationships are defined as those involving two or more of: multi-feature colocation, self-colocation, one-to-many relationships, self-exclusion and multi-feature exclusion. We demonstrate that even in the mining of simple relationships, knowledge of complex relationships is necessary to accurately calculate the significance of results. We implement a representation of spatial data such that it contains known 'weak-monotonic' properties, which are exploited for the efficient mining of complex relationships, and discuss the strengths and limitations of this representation.
AB - This paper describes the need for mining complex relationships in spatial data. Complex relationships are defined as those involving two or more of: multi-feature colocation, self-colocation, one-to-many relationships, self-exclusion and multi-feature exclusion. We demonstrate that even in the mining of simple relationships, knowledge of complex relationships is necessary to accurately calculate the significance of results. We implement a representation of spatial data such that it contains known 'weak-monotonic' properties, which are exploited for the efficient mining of complex relationships, and discuss the strengths and limitations of this representation.
UR - http://www.scopus.com/inward/record.url?scp=18844461110&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:18844461110
SN - 0769519784
SN - 9780769519784
T3 - Proceedings - IEEE International Conference on Data Mining, ICDM
SP - 227
EP - 234
BT - Proceedings - 3rd IEEE International Conference on Data Mining, ICDM 2003
T2 - 3rd IEEE International Conference on Data Mining, ICDM '03
Y2 - 19 November 2003 through 22 November 2003
ER -