Resumen
The article focuses on emerging scientific applications in the field of data mining as of August 1, 2002. Recent progress in scientific and engineering applications has accumulated huge volumes of high-dimensional data, stream data, unstructured and semi-structured data, and spatial and temporal data. Highly scalable and sophisticated data mining tools for such applications represent one of the most active research frontiers in data mining. Efficient technologies of data mining may be specially helpful for fields like biomedical engineering, telecommunications and geospatial exploration and climate and Earth ecosystem modeling. Biology is in the midst of a revolution, with an unprecedented flood of data forcing biologists to rethink their approach to scientific discovery. First, large-scale data-collection techniques have emerged for a number of data sources limited by throughput, or the amount of available data. Data mining flourishes in telecommunications due to the availability of vast quantities of high-quality data. A significant stream of it consists of call records collected at network switches used primarily for billing. The scope, coverage and volume of digital geographic data sets have grown rapidly in recent years due to the progress in data collection and data processing technologies. These data sets include digital data of all sorts, created, processed and disseminated by government and private sector agencies on land use and socioeconomic infrastructure.