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Application of Machine Learning Methods for Cross-Matching Astronomical Catalogues
| Author(s): | Kulishova A., Bryukhov D. O. |
| Published: | Communications in Computer and Information Science: 23rd International Conference: Data Intensive Domains DAMDID/RCDL 2021 (Moscow, Russia, October 26–29, 2021). – Springer, Cham, 2022. Vol. 1620. P. 92–103. |
| Abstract: | |
| The paper presents an approach for the application of machine learning methods for cross-matching astronomical catalogues. Related works on the cross-matching are analyzed and machine learning methods applied are briefly discussed. The approach is applied for cross-matching of three catalogues: Gaia, SDSS and ALLWISE. Experimental results of application of several machine learning methods for cross-matching these catalogues are presented. Recommendations for the application of the approach in astronomical information systems are proposed.
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| Download: |
[ https://link.springer.com/chapter/10.1007/978-3-031-12285-9_6 ]
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