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Efficient SQL-Querying Method for Data Mining in Large Data Bases

Overview Data mining can be understood as a process of extraction of knowledge hidden in very large data sets. Often data mining techniques (e.g. discretization or decision tree) are based on searching for an optimal partition of data with respect to some optimization criterion. This paper investigates the problem of optimal binary partition of continuous attribute domain for large data sets stored in Relational Data Bases (RDB). The critical for time complexity of algorithms solving this problem is the number of simple SQL queries like SELECT COUNT FROM ... WHERE attribute BETWEEN ... (related to some interval of attribute values) necessary to construct such partitions. The paper assumes that the answer time for such queries does not depend on the interval length.

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Publisher
Warsaw University
File Format
PDF
Date Published
Aug 29, 2009
Format
White Papers
Topics
Application Servers, Data Mining - Analysis, Database Management

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