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- W1544352202 abstract "Knowledge discovery methods analyse data of quite diverse types such as cross sections, time series, texts, or multimedia data. We first summarize dimensions being important for identifying subtypes of these main general data types that require special analysis approaches. Thus, specifically for complex, that is, large, high-dimensional, multirelational, or dynamic, data sets problems occur with current views on data developed in statistics and other disciplines. Next, we deal with some organizational forms. Data are not collected as an unregulated set of numbers or strings, but appear in some organized form. Starting at the classical form used in data analysis for organizing cross-sectional data, the flat rectangular organization, we proceed to more complex forms and deal with time and space referenced data. Finally, we treat data aggregation levels and meta data. A classification of data types is useful to select appropriate mining tasks, analysis methods, and data management solutions for an application." @default.
- W1544352202 created "2016-06-24" @default.
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- W1544352202 date "2002-01-01" @default.
- W1544352202 modified "2023-09-23" @default.
- W1544352202 title "Types and forms of data" @default.
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