Name
Abstract | ||
|---|---|---|
A large number of quantitative retrieval models have been proposed in recent years, and there is continuous momentum in proposing new ones. Building a model, from design through to implementation stages, involves a process of knowledge collection, organization and transmission. In this paper we introduce the SECI model to manage the conversion of qualitative remote sensing knowledge and propose a mode of knowledge representation on the basis of the ontology for geospatial modeling. We develop a platform based on the above research and demonstrate the efficiency of the knowledge representation mode using this platform. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/IGARSS.2014.6947493 | IGARSS |
Keywords | DocType | ISSN |
Ontology,remote sensing,geophysics computing,workflow,knowledge transmission,knowledge representation mode,geographic information systems,tacit knowledge,information retrieval,ontology,knowledge management,Remote Sensing,qualitative remote sensing knowledge management,knowledge representation,geospatial modeling,knowledge collection process,knowledge acquisition,remote sensing quantitative retrieval model,ontologies (artificial intelligence),SECI model,knowledge organization,quantitative retrieval models,explicit knowledge,continuous momentum | Conference | 2153-6996 |
Citations | PageRank | References |
1 | 0.37 | 2 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jingzun Zhang | 1 | 1 | 0.37 |
| Yong Xue | 2 | 118 | 57.61 |
| Jing Dong | 3 | 4 | 3.68 |
| Jia Liu | 4 | 10 | 5.97 |
| Longli Liu | 5 | 1 | 0.37 |
| Sahithi Siva | 6 | 1 | 0.37 |
| Jie Guang | 7 | 50 | 26.12 |