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Multidimensional Analysis and Descriptive Mining of Complex Data Objects Set-valued attribute o Generalization of each value in the set into its corresponding higher-level concepts o Derivation of the general behavior of the set, such as the number of elements in the set, the types or value ranges in the set, or the weighted average for numerical data o E.g., hobby = {tennis, hockey, chess, violin, nintendo_games} generalizes to {sports, music, video_games} List-valued or a sequence-valued attribute o Same as set-valued attributes except that the order of the elements in the sequence should be observed in the generalization Aggregation and Approximation in Spatial and Multimedia Data Generalization Aggregation and approximation should be considered another important means of generalization, which is especially useful for generalizing attributes with large sets of values, complex structure and spatial or multimedia data. A multimedia data may contain complex texts,graphics,images,video fragments,maps, voice,music,and other forms of video/audio information. Generalization of object identifies and Class/Subclass Hierarchies Methods are an important component of object-oriented databases. Many behavioral data objects can be derived by the application of methods Spatial data: o Generalize detailed geographic points into clustered regions, such as business, residential, industrial, or agricultural areas, according to land usage o Require the merge of a set of geographic areas by spatial operations Image data: o Extracted by aggregation and/or approximation o Size, color, shape, texture, orientation, and relative positions and structures of the contained objects or regions in the image Music data: o Summarize its melody: based on the approximate patterns that repeatedly occur in the segment o Summarized its style: based on its tone, tempo, or the major musical instruments played