Data mining and knowledge discovery in databases: Applications in astronomy and planetary science
Conference
·
OSTI ID:430913
- One Microsoft Way, Redmond, WA (United States)
Knowledge Discovery in Databases (KDD) is a new field of research concerned with the extraction of high-level information (knowledge) from low-level data (usually stored in large databases). It is an area of interest to researchers and practitioners from many fields including: Al, statistics, pattern recognition, databases, visualization, and high-performance and parallel computing. The basic problem is to search databases for patterns or models that can be useful in accomplishing one or more goals. Examples of such goals include: (1) prediction (e.g. regression and classification), (2) descriptive or generative modeling (e.g. clustering), (3) data summarization (e.g. report generation), or (4) visualization of either data or extracted knowledge (e.g. to support decision making or exploratory data analysis).
- OSTI ID:
- 430913
- Report Number(s):
- CONF-960876--
- Country of Publication:
- United States
- Language:
- English
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