| Author: | Wang, Songsong |
| Title: | Knowledge discovery by spatial clustering rule mining |
| Degree: | M.Sc. |
| Year: | 2007 |
| Subject: | Hong Kong Polytechnic University -- Dissertations. Spatial data infrastructures. Data mining. Geographic information systems. |
| Department: | Department of Land Surveying and Geo-Informatics |
| Pages: | iv, 65 leaves : ill. ; 30 cm. |
| Language: | English |
| Abstract: | In recent years, with the development of data collection technique, data can be obtained form satellite image, X-ray crystallography, and so on. Data is now exploding. We are drowning in information, but starving for knowledge. Spatial data mining is proposed for the knowledge discovery for large data sets. Clustering as one of the major ramification of spatial data mining is in an important status. Clustering has been recognized as a primary data mining method for knowledge discovery in spatial databases. Clustering analysis is widely considered as one of the most important tasks in different research areas. In this paper, a general review of spatial data mining is done first. Second, different representative algorithms of different categories are introduced separately. The general principle, the basic characters, the advantages and the disadvantages of each algorithm are also introduced. At last, a general comparison of these algorithms is done; we also recommend the further directions of clustering algorithms. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b21167874.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 5.93 MB | Adobe PDF | View/Open |
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