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【正文】 in differences lie in the volume of data handled in databases, and in the need to access disk. Specialized datamining algorithms have been developed to handle large volumes of diskresident data efficiently. The manner in which rules are discovered depends on the class of datamining application. We illustrate rule discovery using two application classes: classification and associations. Second. Spatial and Geographic Databases Spatial databases store information related to spatial locations, and provide support for efficient querying and indexing based on spatial locations. Two types of spatial databases are particularly important: Design databases, or puteraideddesign (CAD) databases, are spatial databases used to store design information about how objectssuch as buildings, cars or aircraftare constructed. Other important examples of puteraideddesign databases are integratedcircuit and electronicdevice layouts. Geographic databases are spatial databases used to store geographic information, such as maps. Geographic databases are often called geographic information systems. Geographic data are spatial in nature, but differ from design data in certain ways. Maps and satellite images are typical examples of geographic data. Maps may provide not only location information such as boundaries, rivers and roadsbut also much more detailed information associated with locations, such as elevation, soil type, land usage, and annual rainfall. Geographic data can be categorized into two types: raster data (such data consist a bit maps or pixel maps, in two or more dimensions.), vector data (vector data are constructed from basic geographic objects). Map data are often represented in vector format. Third. Multimedia Databases Recently, there has been much interest in databases that store multimedia data, such as images, audio, and video. Today multimedia data typically are stored outside the database, in files systems. When the number of multimedia objects is relatively small, features provided by databases are usually
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