Framework for Pattern Mining & Prediction of Consumer Behavior Across Websites

Internet provides user the flexibility for selection and shops any product through online transaction. Online transaction is easy way to that makes closer market and consumer. Companies can take competitive advantages by studying the transactions and know the preferences of customer. Due to this increasing demand every retailer wants to make their company more stable. We have developed a tool that will perform analysis of transaction data to understand the pattern and preferences of customer in online transaction. Proposed system performs pattern mining by using association rule mining algorithm. Our proposed system facilitates mining and prediction of online users’ commerce behaviors in order to recommend stores and items previously unknown to a user. We perform an extensive experimental evaluation by simulation and show that our proposals produce excellent results.