A New Scheme for Extracting Association Rules

Moyaid Said, Aiman (2009) A New Scheme for Extracting Association Rules. Masters thesis, Universiti Teknologi PETRONAS.

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Abstract

Data mining is the process of exploring and analyzing large databases to extract
interesting and previously unknown patterns and rules. In the age of information technology,
the amount of accumulated data is tremendous. Extracting the association rule from this data
is one of the important tasks in data mining.
In Data mining, association rule mining is a descriptive technique which can be defined as
discovering meaningful patterns (itemsets tend to take place together in the transactions)
from large collections of data. Mining frequent patterns is a fundamental part of association
rules mining.
Most of the previous studies adopt an a priori-like candidate set generation-and-test
approach to generate the association rules from the transactional database. The priori-like
candidate approach can suffer from two nontrivial costs: it needs to generate a huge number
of candidate sets, and it may need to repeatedly scan the database and check a large set of
candidates by pattern matching.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE: Sciences and Information Technology > Computer and Information Sciences
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 21 Mar 2022 02:09
Last Modified: 21 Mar 2022 02:09
URI: http://utpedia.utp.edu.my/id/eprint/23093

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