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Spatial Data Mining in Settlement Archaeological Databases Based on Vector Features

Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference(2008)

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摘要
The methods of spatial data mining and knowledge discovery (SDMKD) are introduced into the paper on spatial allocation and internal structure of single settlement site of prehistoric settlement archaeology. The spatial database is designed, the Jiangzhai relic map is pretreated by drawing the area and the azimuth from relic such as houses, hearths, pits, urn tombs and pit tombs in the habitation area map in first culture period of Jiangzhai site. With the decision tree classification C4.5 algorithm, this paper makes spatial classification and spatial partition to the relic, draws the rules of classification, and realizes the rapid quantitive analysis for internal structure of single site of settlement archaeology. A simple analysis of clustering algorithm is made. From a different view, paper analyses the distribution rules of each house group and the internal structure of Jiangzhai site. It draws the spatial clustering rules of each type of house group by virtue of k-means clustering algorithm.
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关键词
spatial clustering rule,internal structure,vector features,clustering algorithm,c4.5 algorithm,spatial data mining,single settlement site,visual databases,settlement archaeological,spatial partition,single site,spatial database,archaeology,spatial classification,knowledge discovery,data mining,spatial allocation,decision tree classification,house group,vector feature,jiangzhai site,decision trees,settlement archaeological database,decision tree,clustering algorithms,quantitative analysis,spatial partitioning,c4 5 algorithm,classification algorithms,k means clustering
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