Abstract:
In this paper, frequent pattern mining for Myanmar sculptures gallery is proposed. The proposed system is expects to study the FP-Growth theory, how the transaction database is preprocessed in a way that is common to basically all frequent item set mining algorithm. FP-Growth theory contains a transaction database. Transaction database contains transactions and items. In proposed system, transactions are transaction_Date and items are sculptures category. Sculptures category contains elephant, peacock, dragon, horse, ankone, lawkanaut, women, etc. This proposed system is running the FP-Growth theory, user is request date. And then building the FP-Tree and generating the frequent pattern. This frequent pattern is more seller things in our organization.
