TY - JOUR AU - Frailis, Marco AU - De Angelis, Alessandro AU - Roberto, Vito PY - 2005 DA - 2005/09/14 TI - A Data-Driven Multidimensional Indexing Method for Data Mining in Astrophysical Databases JO - EURASIP Journal on Advances in Signal Processing SP - 841610 VL - 2005 IS - 15 AB - Large archives and digital sky surveys with dimensions of bytes currently exist, while in the near future they will reach sizes of the order of . Numerical simulations are also producing comparable volumes of information. Data mining tools are needed for information extraction from such large datasets. In this work, we propose a multidimensional indexing method, based on a static R-tree data structure, to efficiently query and mine large astrophysical datasets. We follow a top-down construction method, called VAMSplit, which recursively splits the dataset on a near median element along the dimension with maximum variance. The obtained index partitions the dataset into nonoverlapping bounding boxes, with volumes proportional to the local data density. Finally, we show an application of this method for the detection of point sources from a gamma-ray photon list. SN - 1687-6180 UR - https://doi.org/10.1155/ASP.2005.2514 DO - 10.1155/ASP.2005.2514 ID - Frailis2005 ER -