Knowledge discovery by spatial clustering rule mining

Pao Yue-kong Library Electronic Theses Database

Knowledge discovery by spatial clustering rule mining

 

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: Dept. of Land Surveying and Geo-Informatics
Pages: iv, 65 leaves : ill. ; 30 cm.
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b2116787
URI: http://theses.lib.polyu.edu.hk/handle/200/2354
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.

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