Print ISSN: 1681-6900

Online ISSN: 2412-0758

Keywords : closed frequent item sets and maximal frequent item sets

Proposed Enhancement algorithm for Company Employers Management using Genetic Algorithm in Data Mining

Dalia Nabeel Kamal

Engineering and Technology Journal, 2010, Volume 28, Issue 2, Pages 261-270

Data mining is a process of automatically discovering useful information in
large data repositories that uses a variety of data analysis tools to discover patterns
and relationships that can be hidden among vast amount of data. From these
patterns and relationships, businesses and organizations can make valid
predictions about future trends in all areas of business. Association rule mining is
a typical approach used in data mining domain for uncovering interesting trends,
patterns and rules in large datasets.
This research concentrates on one particular aspect to improve the efficiency of
the association rules technique in data mining and implement the proposed
algorithm on employers management system. The resulted association which
introduced by applying rule technique, will be treated by genetic algorithm to find
a new rules that might be more efficient and powerful for proposed data base by
propose cross point ,threshold for fitness to deal consistently with the formula of
the association rules, and gives good results.