机构:
Carnegie Mellon Univ, Sch Comp Sci, Pittsburgh, PA 15213 USACarnegie Mellon Univ, Sch Comp Sci, Pittsburgh, PA 15213 USA
Chuah, MC
[1
]
机构:
[1] Carnegie Mellon Univ, Sch Comp Sci, Pittsburgh, PA 15213 USA
来源:
IEEE SYMPOSIUM ON INFORMATION VISUALIZATION - PROCEEDINGS
|
1998年
关键词:
D O I:
10.1109/INFVIS.1998.729557
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
One very effective method for managing large data sets is aggregation or binning. In this paper we consider two aggregation methods that are tightly coupled with interactive manipulation and the visual representation of the data. Through this integration we hope to provide effective support for the aggregation process, specifically by enabling: 1) automatic aggregation 2) continuous change and control of the aggregation level, 3) spatially based aggregates, 4) context maintenance across different aggregate levels, and 5) feedback on the level of aggregation.