Mining Regular Pattern Over Dynamic Data Stream Using Bit Stream Sequence

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Provided by: International Journal of Innovative Technology and Exploring Engineering (IJITEE)
Topic: Data Management
Format: PDF
In recent years, data streams have become an increasingly important area of research for the computer science, database and data mining communities. Data streams are ordered and potentially unbounded sequences of data points created by a typically non-stationary generation process. Common data mining tasks associated with data streams include clustering, classification and frequent pattern mining. Recently, temporal regularity in occurrence behavior of a pattern was treated as an emerging area in several applications. A pattern is said to be regular in a data stream, if its occurrence behavior is not more than the user given regularity threshold.
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