Analysis and Comparison of Data Mining Tools Using Case Study of Library Management System
Keywords:
ARM, ARMADA, data warehouse, data mart.Abstract
The term data mining has been the oldest yet one
of the interesting buzzwords. Many organizations often
underutilize their already existing databases. There is a need to
mine information and interesting patterns from these databases.
The focus of the current research is to apply data mining on a
library management system. Data mining is usually done on a
data warehouse or a data mart. It incurs various cost factors
like software, hardware, maintenance and experts. The
objective here is to study how the real-time data stored in
database can be turned informative without setting up a
separate data warehouse. The main emphasize is on
understanding the problem perspective, competing objectives
and constraints and generating a model for information
extraction from the real-time library database using ARM
(Association Rule Mining) mining technique. As SQL
(Structured Query Language) can also be used for mining data
instead of using specialized data mining algorithm [1], the study
also compares SQL based mining with ARM. The results shows
that association rule mining performs better than SQL based
mining as type of pattern to be extracted can be controlled
much effectively in ARM as compared to SQL because of the
parameters (support and count) used in the data mining
algorithm. Algorithms are implemented using SQL and
MATLAB (Matrix Laboratory) Tool - ARMADA.
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