Implementation of Myanmar Sculptures Gallery By using Frequent Pattern Mining

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.