数据库和仓库中聚类和查询的几何方法

O. Sourina, Dongquan Liu
{"title":"数据库和仓库中聚类和查询的几何方法","authors":"O. Sourina, Dongquan Liu","doi":"10.1109/CYBER.2003.1253472","DOIUrl":null,"url":null,"abstract":"Databases and warehouses play significant role in real world providing the human with the necessary information for solving problems in all areas of life from marketing to bioinformatics. Therefore, databases and warehouses are essential components of all intelligent information systems in cyberworlds. This paper describes a geometric approach to clustering and querying data in databases and warehouses. Data are interpreted geometrically as multidimensional points. A geometric definition of the cluster as a multidimensional solid defined with implicit functions is introduced. A query window is a query solid of any shape specified by its location. The queries are formulated with geometric objects and operations over them. The geometric objects and operations are described with implicit functions. With the uniform geometric model of the clustering and querying, 3D visualization tools can be naturally incorporated in one system that allows us to visualize and query clusters in 3D space. The user clusters the data and poses the queries through a graphics interface accessing dynamically multidimensional points and solids.","PeriodicalId":130458,"journal":{"name":"Proceedings. 2003 International Conference on Cyberworlds","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Geometric approach to clustering and querying in databases and warehouses\",\"authors\":\"O. Sourina, Dongquan Liu\",\"doi\":\"10.1109/CYBER.2003.1253472\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Databases and warehouses play significant role in real world providing the human with the necessary information for solving problems in all areas of life from marketing to bioinformatics. Therefore, databases and warehouses are essential components of all intelligent information systems in cyberworlds. This paper describes a geometric approach to clustering and querying data in databases and warehouses. Data are interpreted geometrically as multidimensional points. A geometric definition of the cluster as a multidimensional solid defined with implicit functions is introduced. A query window is a query solid of any shape specified by its location. The queries are formulated with geometric objects and operations over them. The geometric objects and operations are described with implicit functions. With the uniform geometric model of the clustering and querying, 3D visualization tools can be naturally incorporated in one system that allows us to visualize and query clusters in 3D space. The user clusters the data and poses the queries through a graphics interface accessing dynamically multidimensional points and solids.\",\"PeriodicalId\":130458,\"journal\":{\"name\":\"Proceedings. 2003 International Conference on Cyberworlds\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-12-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 2003 International Conference on Cyberworlds\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CYBER.2003.1253472\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 2003 International Conference on Cyberworlds","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CYBER.2003.1253472","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

摘要

数据库和仓库在现实世界中扮演着重要的角色,为人类解决从市场营销到生物信息学等生活各个领域的问题提供必要的信息。因此,数据库和仓库是网络世界中所有智能信息系统的重要组成部分。本文描述了一种在数据库和仓库中聚类和查询数据的几何方法。数据在几何上被解释为多维点。引入了聚类的几何定义,将聚类定义为用隐函数定义的多维实体。查询窗口是由其位置指定的任何形状的查询实体。查询是用几何对象和对它们的操作来表示的。几何对象和运算用隐函数描述。有了统一的聚类和查询的几何模型,三维可视化工具可以自然地整合到一个系统中,使我们能够在三维空间中可视化和查询聚类。用户通过动态访问多维点和实体的图形界面对数据进行聚类并提出查询。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geometric approach to clustering and querying in databases and warehouses
Databases and warehouses play significant role in real world providing the human with the necessary information for solving problems in all areas of life from marketing to bioinformatics. Therefore, databases and warehouses are essential components of all intelligent information systems in cyberworlds. This paper describes a geometric approach to clustering and querying data in databases and warehouses. Data are interpreted geometrically as multidimensional points. A geometric definition of the cluster as a multidimensional solid defined with implicit functions is introduced. A query window is a query solid of any shape specified by its location. The queries are formulated with geometric objects and operations over them. The geometric objects and operations are described with implicit functions. With the uniform geometric model of the clustering and querying, 3D visualization tools can be naturally incorporated in one system that allows us to visualize and query clusters in 3D space. The user clusters the data and poses the queries through a graphics interface accessing dynamically multidimensional points and solids.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信