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by Haixun Wang, Carlo Zaniolo
http://www.cs.ucr.edu/~dg/wang.ps
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Abstract:
Research on database-centric data mining is seeking to improve the effectiveness of database systems in decision support applications. Different solutions are now used for different problems, including (i) SQL extensions for more complex OLAP queries, (ii) new datablades for special data types such as time-series, and (iii) architectural extensions to support data mining functions. Here, we proposed a unified solution for all these problems; the solution is based on User-Defined Aggregates (UDAs) expressed in an SQL-like language called AXL. In this paper, we discuss the architecture and implementation of the AXL prototype and its use and performance in expressing data mining functions and complex OLAP queries. 1
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