Virtual Observatories, Data Mining, and Astroinformatics
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[1] G. Abell. The Distribution of rich clusters of galaxies , 1958 .
[2] S. Sharpless. A Catalogue of H II Regions. , 1959 .
[3] B. T. Lynds. Catalogue of Dark Nebulae. , 1962 .
[4] W. L. Sebok,et al. Optimal classification of images into stars or galaxies - a Bayesian approach. , 1979 .
[5] S. Djorgovski,et al. Fundamental Properties of Elliptical Galaxies , 1987 .
[6] R. Davies,et al. Spectroscopy and photometry of elliptical galaxies. I: a new distance estimator , 1987 .
[7] Simon Kasif,et al. A System for Induction of Oblique Decision Trees , 1994, J. Artif. Intell. Res..
[8] J. Ross Quinlan,et al. Bagging, Boosting, and C4.5 , 1996, AAAI/IAAI, Vol. 1.
[9] David Bazell,et al. A Comparison of Neural Network Algorithms and Preprocessing Methods for Star-Galaxy Discrimination , 1998 .
[10] Kirk D. Borne. Data Mining in Astronomical Databases , 2000, ArXiv.
[11] F. Ochsenbein,et al. The VizieR database of astronomical catalogues , 2000, astro-ph/0002122.
[12] Robert J. Brunner,et al. Massive datasets in astronomy , 2001 .
[13] Robert J. Brunner,et al. The National Virtual Observatory , 2001 .
[14] Robert J. Brunner,et al. Exploration of parameter spaces in a virtual observatory , 2001, SPIE Optics + Photonics.
[15] Alexander S. Szalay,et al. Petabyte Scale Data Mining: Dream or Reality? , 2002, SPIE Astronomical Telescopes + Instrumentation.
[16] Anne E. Trefethen,et al. The UK e-Science Core Programme and the Grid , 2002, Future Gener. Comput. Syst..
[17] Kirk D. Borne. Distributed data mining in the National Virtual Observatory , 2003, SPIE Defense + Commercial Sensing.
[18] Applicability of Emerging Resource Discovery Standards to the VO , 2004 .
[19] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[20] A. Cimatti,et al. A catalogue of the Chandra Deep Field South with multi-colour classification and photometric redshifts from COMBO-17 , 2004, astro-ph/0403666.
[21] Alexander S. Szalay,et al. Where the Rubber Meets the Sky: Bridging the Gap between Databases and Science , 2004, IEEE Data Eng. Bull..
[22] F. Ochsenbein,et al. Astronomical Data Analysis Software and Systems (ADASS) XIII , 2004 .
[23] Kirk D. Borne,et al. eScience and archiving for space science , 2005, Data Sci. J..
[24] J. Peacock,et al. Simulations of the formation, evolution and clustering of galaxies and quasars , 2005, Nature.
[25] R. Missaoui,et al. Similarity measures for efficient content-based image retrieval , 2005 .
[26] An exact equilibrium model of an unbound stellar system in a tidal field , 2005, astro-ph/0502374.
[27] Robert G. Raskin,et al. Knowledge representation in the semantic web for Earth and environmental terminology (SWEET) , 2005, Comput. Geosci..
[28] Alexander S. Szalay,et al. Designing a multi-petabyte database for LSST , 2005, SPIE Astronomical Telescopes + Instrumentation.
[29] Alexander S. Szalay,et al. Petascale computational systems , 2007, Computer.
[30] Robert J. Brunner,et al. Robust Machine Learning Applied to Astronomical Data Sets. I. Star-Galaxy Classification of the Sloan Digital Sky Survey DR3 Using Decision Trees , 2006, astro-ph/0606541.
[31] Matthew J. Graham,et al. The National Virtual Observatory: Tools and Techniques for Astronomical Research , 2007 .
[32] L. M. Sarro,et al. Automated supervised classification of variable stars - I. Methodology , 2007, 0711.0703.
[33] Joel H. Kastner,et al. An X-Ray Spectral Classification Algorithm with Application to Young Stellar Clusters , 2007 .
[34] Kirk D. Borne. A machine learning classification broker for the LSST transient database , 2008 .
[35] Richard L. White. Astronomical Applications of Oblique Decision Trees , 2008 .
[36] C. Aerts,et al. Automated supervised classification of variable stars II. Application to the OGLE database , 2008, 0806.3386.
[37] Gamma-ray Bursts, Classified Physically , 2008, 0804.0965.
[38] K. D. Borne,et al. The LSST Data Mining Research Agenda , 2008, 0811.0167.
[39] Pavlos Protopapas,et al. Finding anomalous periodic time series , 2009, Machine Learning.
[40] et al,et al. Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS , 2008 .
[41] William Gropp,et al. Applied Mathematics at the U.S. Department of Energy: Past, Present and a View to the Future , 2008 .
[42] J. Bloom,et al. Towards a Real-time Transient Classification Engine , 2008, 0802.2249.
[43] G. Rossi,et al. Unbiased estimates of galaxy scaling relations from photometric redshift surveys , 2007, 0710.1165.
[44] Timothy E. Eastman,et al. Complementary Frameworks of Scientific Inquiry: Hypothetico-Deductive, Hypothetico-Inductive, and Observational-Inductive , 2009 .
[45] Comment: Preserving digital data for the future of escience , 2009 .
[46] Arie Shoshani,et al. Scientific Data Management - Challenges, Technology, and Deployment , 2009, Scientific Data Management.
[47] A. Szalay,et al. GALEX–SDSS CATALOGS FOR STATISTICAL STUDIES , 2009, 0904.1392.
[48] Canada.,et al. Data Mining and Machine Learning in Astronomy , 2009, 0906.2173.
[49] Xindong Wu,et al. The Top Ten Algorithms in Data Mining , 2009 .
[50] A. J. Drake,et al. FIRST RESULTS FROM THE CATALINA REAL-TIME TRANSIENT SURVEY , 2008, 0809.1394.
[51] A. Nobel,et al. Finding large average submatrices in high dimensional data , 2009, 0905.1682.
[52] Kirk D. Borne,et al. Astroinformatics: A 21st Century Approach to Astronomy , 2009, ArXiv.
[53] John Elder,et al. Handbook of Statistical Analysis and Data Mining Applications , 2009 .
[54] Alexander S. Szalay,et al. RANDOM FORESTS FOR PHOTOMETRIC REDSHIFTS , 2010 .
[55] Kirk D. Borne. Astroinformatics: data-oriented astronomy research and education , 2010, Earth Sci. Informatics.
[56] V. Trimble,et al. Productivity and impact of astronomical facilities: A recent sample , 2010 .
[57] Doug Tody,et al. Building archives in the virtual observatory era , 2010, Astronomical Telescopes + Instrumentation.
[58] K. Pimbblet. Backsplash galaxies in isolated clusters , 2010, 1010.3468.
[59] Jordan Raddick,et al. Galaxy Zoo: Morphological Classification and Citizen Science , 2011, 1104.5513.
[60] Kirk D. Borne,et al. Scalable, asynchronous, distributed eigen monitoring of astronomy data streams , 2011, Stat. Anal. Data Min..
[61] Ian H. Witten,et al. Chapter 1 – What's It All About? , 2011 .
[62] L. Paioro,et al. Simple Application Messaging Protocol Version 1.3 , 2011, 1110.0528.
[63] Kirk D. Borne,et al. Surprise Detection in Multivariate Astronomical Data , 2012 .
[64] Daniel T. Larose,et al. Discovering Knowledge in Data: An Introduction to Data Mining , 2005 .