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Author(s): C. L. Curotto & N. F. F. Ebecken
Abstract:
One of the most useful features of the Object Linking and Embedding Database
for Data Mining technology, a standard for implementation of data mining
algorithms aggregated with Microsoft® SQL Server™, is the ability of using
nested data mining columns, providing an affordable and efficient way to
support relational data models.
A brief overview of the common approaches used
to deal with multi-relational data mining is presented.
Experiments are carried
out, using the SQL Server™ 2000 release as well as its new 2005 Beta 2 version,
to evaluate the capability of these tools while dealing with multi-relational data
mining.
In these experiments the Microsoft® Decision Trees data mining
algorithm is considered.
Keywords:
multi-relational, data mining, algorithm, decision trees, database,
sql, server, nested tables.
1 Introduction:
To achieve the tight coupling of Data Mining (DM) techniques in Database
Management Systems (DBMS) technology, a number of approaches have been
developed in the last years.
These approaches include solutions provided by both
company and academic research groups.
Toward this objective, the Microsoft® (MS) Object Linking and Embedding
Database for DM (OLE DB DM) technology [1] provides an industry standard
for developing DM algorithms.
This technology was included in the MS SQL
Server™ (MSSQL) 2000 release [2].
The Analysis Services (AS) component of
this software includes a DM provider supporting two algorithms: one for
classification by decision trees [3] and another for clustering [4].
The DM
...
Pages: 10
Size: 1,017 kb
Paper DOI: 10.2495/DATA050221
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