{"title":"用于空间集群的可扩展工具","authors":"Venny Larasati Ayudiani, Saiful Akbar","doi":"10.1109/ICODSE.2017.8285848","DOIUrl":null,"url":null,"abstract":"Spatial clustering dealt with the clustering of spatial objects so that the objects with higher similarity is grouped together in a cluster. It has been applied among numerous fields with various approaches and methods. Some tools and libraries capable of doing spatial clustering analysis have been developed. However, those tools typically only implement a specific approach. In this paper, we propose a user-friendly analysis tool that can facilitate various approaches and methods to conduct spatial clustering analysis. Moreover, we take into account the extensibility factor of the analysis tool which allows integration of new algorithms to be done.","PeriodicalId":366005,"journal":{"name":"2017 International Conference on Data and Software Engineering (ICoDSE)","volume":"231 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An extensible tool for spatial clustering\",\"authors\":\"Venny Larasati Ayudiani, Saiful Akbar\",\"doi\":\"10.1109/ICODSE.2017.8285848\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Spatial clustering dealt with the clustering of spatial objects so that the objects with higher similarity is grouped together in a cluster. It has been applied among numerous fields with various approaches and methods. Some tools and libraries capable of doing spatial clustering analysis have been developed. However, those tools typically only implement a specific approach. In this paper, we propose a user-friendly analysis tool that can facilitate various approaches and methods to conduct spatial clustering analysis. Moreover, we take into account the extensibility factor of the analysis tool which allows integration of new algorithms to be done.\",\"PeriodicalId\":366005,\"journal\":{\"name\":\"2017 International Conference on Data and Software Engineering (ICoDSE)\",\"volume\":\"231 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Data and Software Engineering (ICoDSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICODSE.2017.8285848\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference on Data and Software Engineering (ICoDSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICODSE.2017.8285848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatial clustering dealt with the clustering of spatial objects so that the objects with higher similarity is grouped together in a cluster. It has been applied among numerous fields with various approaches and methods. Some tools and libraries capable of doing spatial clustering analysis have been developed. However, those tools typically only implement a specific approach. In this paper, we propose a user-friendly analysis tool that can facilitate various approaches and methods to conduct spatial clustering analysis. Moreover, we take into account the extensibility factor of the analysis tool which allows integration of new algorithms to be done.