Data mining and knowledge discovery resources for astronomy in the web 2.0 age

  title={Data mining and knowledge discovery resources for astronomy in the web 2.0 age},
  author={Stefano Cavuoti and Massimo Brescia and Giuseppe Longo},
  booktitle={Other Conferences},
The emerging field of AstroInformatics, while on the one hand appears crucial to face the technological challenges, on the other is opening new exciting perspectives for new astronomical discoveries through the implementation of advanced data mining procedures. The complexity of astronomical data and the variety of scientific problems, however, call for innovative algorithms and methods as well as for an extreme usage of ICT technologies. The DAME (DAta Mining and Exploration) Program exposes a… 

C3, A Command-line Catalog Cross-match Tool for Large Astrophysical Catalogs

It is verified that the C 3 tool has excellent capabilities to perform an efficient and reliable cross-matching between large data sets, and makes C 3 competitive in the context of public astronomical tools.



DAME: A Web Oriented Infrastructure for Scientific Data Mining & Exploration

DAME (DAta Mining & Exploration) is an innovative, general purpose, Web-based, VObs compliant, distributed data mining infrastructure specialized in Massive Data Sets exploration with machine learning methods.

The DAME/VO-Neural Infrastructure: an Integrated Data Mining System Support for the Science Community

The result of the DAME/VO-Neural project effort will be a service-oriented architecture, obtained by using appropriate standards and incorporating Grid paradigms and restful Web services frameworks where needed, that will have as main target the integration of interdisciplinary distributed systems within and across organizational domains.

Chimera: a virtual data system for representing, querying, and automating data derivation

The Chimera virtual data system is developed, which combines avirtual data catalog for representing data derivation procedures and derived data, with a virtual data language interpreter that translates user requests into data definition and query operations on the database.

The detection of globular clusters in galaxies as a data mining problem

An extensive set of experiments revealed that the use of accurate structural parameters does improve the result, but only by ∼5%.


In the past ten years, the concept of Virtual Obser vato y (VObs) has increasingly gained importance in the domain of astrophysics, as a way of seamlessly accessing data in different wavelength

Probabilistic principal surfaces for yeast gene microarray data mining

Probabilistic principal surfaces (PPS) is proposed as an effective high-D data visualization and clustering tool for data mining applications, emphasizing its flexibility and generality of use in data-rich field.

Mining the SDSS Archive. I. Photometric Redshifts in the Nearby Universe

We present a supervised neural network approach to the determination of photometric redshifts. The method was fine-tuned to match the characteristics of the Sloan Digital Sky Survey, and as base of

Quasar candidates selection in the Virtual Observatory era

We present a method for the photometric selection of candidate quasars in multiband surveys. The method makes use of a priori knowledge derived from a subsample of spectroscopic confirmed

Photometric redshifts with Quasi Newton Algorithm (MLPQNA). Results in the PHAT1 contest

Context. Since the advent of modern multiband digital sky surveys, photometric redshifts (photo-z's) have become relevant if not crucial to many fields of observational cosmology, from the