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Temporal Categorization for Data Organization
Abstract
Temporal databases are designed to handle records that are time-oriented. While the additional dimension produces data that is rich in meaning, capturing this history results in large volumes of data that are rarely used. Previous research has found that the additional data can impair system performance when attempting to use temporal databases as operational systems. This paper presents the conceptual work done in an area that the authors have termed, temporal categorization, which involves a method of data organization that groups records according to their unique temporal semantics. The different ways of categorizing temporal data, including the benefits and challenges, are described in the paper.
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