Interactive Visualization of Large High-Dimensional Datasets

Wei Ding and Ping Chen
Additional contact information
Wei Ding: University of Massachusetts Boston
Ping Chen: University of Houston Downtown

Chapter 15 in Data Engineering, 2009, pp 335-351 from Springer

Abstract: Abstract Nowadays many companies and public organizations use powerful database systems for collecting and managing information. Huge amount of data records are often accumulated within a short period of time. Valuable information is embedded in these data, which could help discover interesting knowledge and significantly assist in decision-making process. However, human beings are not capable of understanding so many data records which often have lots of attributes. The need for automated knowledge extraction is widely recognized, and leads to a rapidly developing market of data analysis and knowledge discovery tools.

Keywords: Data Dimension; Visual Object; Transformation Function; Visualization System; Interactive Visualization (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-1-4419-0176-7_15

Ordering information: This item can be ordered from
http://www.springer.com/9781441901767

DOI: 10.1007/978-1-4419-0176-7_15

Access Statistics for this chapter

More chapters in International Series in Operations Research & Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().