Affiliation:
1. GeoMiner Research Group, Database Systems Research Laboratory, School of Computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6
Abstract
Spatial data mining is to mine high-level spatial information and knowledge from large spatial databases. A spatial data mining system prototype, GeoMiner, has been designed and developed based on our years of experience in the research and development of relational data mining system, DBMiner, and our research into spatial data mining. The data mining power of GeoMiner includes mining three kinds of rules:
characteristic rules, comparison rules
, and
association rules
, in geo-spatial databases, with a planned extension to include mining
classification rules
and
clustering rules
. The
SAND
(
Spatial And Nonspatial Data
) architecture is applied in the modeling of spatial databases, whereas GeoMiner includes the
spatial data cube construction module
,
spatial on-line analytical processing
(
OLAP
)
module
, and
spatial data mining modules
. A spatial data mining language, GMQL (
Geo-Mining Query Language
), is designed and implemented as an extension to
Spatial SQL
[3], for spatial data mining. Moreover, an interactive, user-friendly data mining interface is constructed and tools are implemented for visualization of discovered spatial knowledge.
Publisher
Association for Computing Machinery (ACM)
Subject
Information Systems,Software
Reference14 articles.
1. M. S. Chen J. Han and P. S. Yu. Data mining: An overview from a database perspective. IEEE Trsnsactions on Knowledge a~d Data Engineering 8:866-883 1906. 10.1109/69.553155 M. S. Chen J. Han and P. S. Yu. Data mining: An overview from a database perspective. IEEE Trsnsactions on Knowledge a~d Data Engineering 8:866-883 1906. 10.1109/69.553155
2. Spatial SQL: a query and presentation language
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