Details
| Originalsprache | Englisch |
|---|---|
| Fachzeitschrift | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Jahrgang | 35 |
| Publikationsstatus | Veröffentlicht - 2004 |
| Veranstaltung | 20th ISPRS Congress on Technical Commission VII - Istanbul, Türkei Dauer: 12 Juli 2004 → 23 Juli 2004 |
Abstract
Geographical data sets contain a huge amount of information about spatial phenomena. The exploitation of this knowledge with the aim to make it usable in an internet search engine is one of the goals of the EU-funded project SPIRIT. This project deals with spatially related information retrieval in the internet and the development of a search engine, which includes the spatial aspect of queries. Existing metadata as provided by the standard ISO/DIS 19115 only give fractional information about the substantial content of a data set. Most of the time, the enrichment with metadata has to be done manually, which results in this information being present rarely. Further, the given metadata does not contain implicit information. This implicit information does not exist on the level of pure geographical features, but on the level of the relationships between the features, their extent, density, frequency, neighbourhood, uniqueness and more. This knowledge often is well known by humans with their background information, however it has to be made explicit for the computer. The first part of the paper describes the automatic extraction of classical metadata from data sets. The second part describes concepts of information retrieval from geographical data sets. This part deals with the setup of rules to derive useful implicit information. We describe possible implementations of data mining algorithms.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Information systems
- Sozialwissenschaften (insg.)
- Geografie, Planung und Entwicklung
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in: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Jahrgang 35, 2004.
Publikation: Beitrag in Fachzeitschrift › Konferenzaufsatz in Fachzeitschrift › Forschung › Peer-Review
}
TY - JOUR
T1 - Derivation of implicit information from spatial data sets with data mining
AU - Heinzle, Frauke
AU - Sester, Monika
PY - 2004
Y1 - 2004
N2 - Geographical data sets contain a huge amount of information about spatial phenomena. The exploitation of this knowledge with the aim to make it usable in an internet search engine is one of the goals of the EU-funded project SPIRIT. This project deals with spatially related information retrieval in the internet and the development of a search engine, which includes the spatial aspect of queries. Existing metadata as provided by the standard ISO/DIS 19115 only give fractional information about the substantial content of a data set. Most of the time, the enrichment with metadata has to be done manually, which results in this information being present rarely. Further, the given metadata does not contain implicit information. This implicit information does not exist on the level of pure geographical features, but on the level of the relationships between the features, their extent, density, frequency, neighbourhood, uniqueness and more. This knowledge often is well known by humans with their background information, however it has to be made explicit for the computer. The first part of the paper describes the automatic extraction of classical metadata from data sets. The second part describes concepts of information retrieval from geographical data sets. This part deals with the setup of rules to derive useful implicit information. We describe possible implementations of data mining algorithms.
AB - Geographical data sets contain a huge amount of information about spatial phenomena. The exploitation of this knowledge with the aim to make it usable in an internet search engine is one of the goals of the EU-funded project SPIRIT. This project deals with spatially related information retrieval in the internet and the development of a search engine, which includes the spatial aspect of queries. Existing metadata as provided by the standard ISO/DIS 19115 only give fractional information about the substantial content of a data set. Most of the time, the enrichment with metadata has to be done manually, which results in this information being present rarely. Further, the given metadata does not contain implicit information. This implicit information does not exist on the level of pure geographical features, but on the level of the relationships between the features, their extent, density, frequency, neighbourhood, uniqueness and more. This knowledge often is well known by humans with their background information, however it has to be made explicit for the computer. The first part of the paper describes the automatic extraction of classical metadata from data sets. The second part describes concepts of information retrieval from geographical data sets. This part deals with the setup of rules to derive useful implicit information. We describe possible implementations of data mining algorithms.
KW - Data mining
KW - Databases
KW - GIS
KW - Information
KW - Internet/Web
KW - Metadata
KW - Retrieval
KW - Spatial
UR - http://www.scopus.com/inward/record.url?scp=84929707156&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84929707156
VL - 35
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SN - 1682-1750
T2 - 20th ISPRS Congress on Technical Commission VII
Y2 - 12 July 2004 through 23 July 2004
ER -