Abstract:
This paper is presented the mining
association rules among items in a large database
of sales transactions. The mining of association
rules can be mapped into the problem of
discovering large itemsets which appear in a
sufficient number of transactions. Association rule
mining plays an essential role in data mining. The
knowledge used for mining rule depends on
time(month, season) in real world and so calendar
based association rule is needed to consider.
Calendar pattern is used to restrict the time
interval. Calendar based association rules is an
interesting extension to association rules by
including a calendar pattern. Frequent-Pattern
Growth (FP-Growth) algorithm is used to
generate the calendar based association rules.
FP-Growth is a method of mining frequent
itemsets without candidate generation. The system
generates the calendar based association rule
using FP-Growth algorithm and analyze on the
result.
