Abstract
Astronomers have always classified celestial objects. The ancient Greeks distinguished between asteros, the fixed stars, and planetos, the roving stars. The latter were associated with the Gods and, starting with Plato in his dialog Timaeus, provided the first mathematical models of celestial phenomena. Giovanni Hodierna classified nebulous objects, seen with a Galilean refractor telescope in the mid-seventeenth century into three classes: “Luminosae, " “Nebulosae, " and “Occultae.” A century later, Charles Messier compiled a larger list of nebulae, star clusters and galaxies, but did not attempt a classification. Classification of comets was a significant enterprise in the 19th century: Alexander (1850) considered two groups based on orbit sizes, Lardner (1853) proposed three groups of orbits, and Barnard (1891) divided them into two classes based on morphology.
Original language | English (US) |
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Title of host publication | Advances in Machine Learning and Data Mining for Astronomy |
Publisher | CRC Press |
Pages | 3-10 |
Number of pages | 8 |
ISBN (Electronic) | 9781439841747 |
ISBN (Print) | 9781138199309 |
DOIs | |
State | Published - Jan 1 2012 |
All Science Journal Classification (ASJC) codes
- General Computer Science
- General Physics and Astronomy