Mining Quasar Candidates from Large Sky Surveys
Yanxia Zhang, Ali Luo, Yongheng Zhao
National Astronomical Observatory,CAS, Beijing, China

With the development and operation of various large sky survey projects, how to improve and optimize the efficiency and scientific output of telescopes is a hot issue. Thus the careful preparation of survey programs and input catalogs are of great value. The development of robust data mining techniques for ground-based instruments (such as Chinese LAMOST telescope) is a key element in preselecting quasar candidates from other photometric surveys. Taking quantity and complexity of astronomical data into account, a large number of mining approaches are applied and compared to create the quasar targeting catalog. Each method has its merits and demerits.

Keywords: Catalogs; Methods statistical; Quasars: General; Survey

Biography: I major in classification and clustering of celestial objects, the multi-wavelength properties of all kinds of objects, cross-match multiwavelength catalog and data mining and knowledge discovery in astronomy.