The development of predictive applications built on top of knowledge bases is rapidly growing, therefore database systems, especially the commercial ones, are boosting with native data mining analytical tools. In this paper, we present an integration of data mining primitives on top of MySQL 5.1. In particular, we extended MySQL to support frequent itemsets computation and classification based on C4.5 decision trees. These commands are recognized by the parser that has been properly extended to support new SQL statements. Moreover, the implemented algorithms were engineered and integrated in the source code of MySQL in order to allow large-scale applications and a fast response time. Finally, a graphical interface guides the user to explore the new data mining facilities.
MySQL Data Mining: Extending MySQL to Support Data Mining Primitives
GIUGNO, ROSALBA;
2010-01-01
Abstract
The development of predictive applications built on top of knowledge bases is rapidly growing, therefore database systems, especially the commercial ones, are boosting with native data mining analytical tools. In this paper, we present an integration of data mining primitives on top of MySQL 5.1. In particular, we extended MySQL to support frequent itemsets computation and classification based on C4.5 decision trees. These commands are recognized by the parser that has been properly extended to support new SQL statements. Moreover, the implemented algorithms were engineered and integrated in the source code of MySQL in order to allow large-scale applications and a fast response time. Finally, a graphical interface guides the user to explore the new data mining facilities.
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