{"title":"变密度空间数据聚类","authors":"R. K. Prasad, R. Sarmah","doi":"10.1109/ICCCT.2011.6075127","DOIUrl":null,"url":null,"abstract":"This paper presents an effective clustering method which can detect embedded and nested clusters over variable density space. The proposed method, VDSC uses a density based approach for detecting clusters of arbitrary shapes, sizes and densities. VDSC was compared with several other comparable algorithms and the experimental results show that our method could detect all clusters effectively.","PeriodicalId":285986,"journal":{"name":"2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Variable density spatial data clustering\",\"authors\":\"R. K. Prasad, R. Sarmah\",\"doi\":\"10.1109/ICCCT.2011.6075127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an effective clustering method which can detect embedded and nested clusters over variable density space. The proposed method, VDSC uses a density based approach for detecting clusters of arbitrary shapes, sizes and densities. VDSC was compared with several other comparable algorithms and the experimental results show that our method could detect all clusters effectively.\",\"PeriodicalId\":285986,\"journal\":{\"name\":\"2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011)\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCT.2011.6075127\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCT.2011.6075127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents an effective clustering method which can detect embedded and nested clusters over variable density space. The proposed method, VDSC uses a density based approach for detecting clusters of arbitrary shapes, sizes and densities. VDSC was compared with several other comparable algorithms and the experimental results show that our method could detect all clusters effectively.