Paper
15 July 2008 Knowledge discovery in astronomical data
Author Affiliations +
Abstract
With the construction and development of ground-based and space-based observatories, astronomical data amount to Terascale, even Petascale. How to extract knowledge from so huge data volume by automated methods is a big challenge for astronomers. Under this situation, many researchers have studied various approaches and developed different softwares to solve this issue. According to the special task of data mining, we need to select an appropriate technique suiting the requirement of data characteristics. Moreover all algorithms have their own pros and cons. We introduce the characteristics of astronomical data, present the taxonomy of knowledge discovery, and describe the functionalities of knowledge discovery in detail. Then the methods of knowledge discovery are touched upon. Finally the successful applications of data mining techniques in astronomy are summarized and reviewed. Facing data avalanche in astronomy, knowledge discovery in databases (KDD) shows its superiority.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yanxia Zhang, Hongwen Zheng, and Yongheng Zhao "Knowledge discovery in astronomical data", Proc. SPIE 7019, Advanced Software and Control for Astronomy II, 701938 (15 July 2008); https://doi.org/10.1117/12.788417
Lens.org Logo
CITATIONS
Cited by 6 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Astronomy

Knowledge discovery

Data mining

Galactic astronomy

Statistical analysis

Databases

Data modeling

RELATED CONTENT

Outlier detection in astronomical data
Proceedings of SPIE (September 16 2004)
Intelligent system to study demographic evolution
Proceedings of SPIE (February 25 1999)
Mining the LAMOST spectral archive
Proceedings of SPIE (September 16 2004)

Back to Top