论文信息 - Online Store Product Recommendation System Uses Apriori Method

Online Store Product Recommendation System Uses Apriori Method

Online Store grows very fast. Online Store helps people to buy the desired product online. Heavy competition among of Online Store provider give a rise to technology development. Many Online Store system not only display the product but also need to be supported by proper products selection to attract the attention of website visitors. As a result, many website visitors are confused when they are going to buy products in Online Store. The number of product variety offered to a customer when he buys goods sometimes more than one product. The problem leads to an idea of developing a products recommendation system. Historical data from visitors and customers can be used to analyze the user needs and products preferences. Association rule using Apriori knowledge will be able to capture the user preference. By identify the user preferences, a valid product recommendation can be developed. This research will analyze the rules in a historical data of purchase from Online Store visitors to get recommendation of products to be displayed. According to experiment result, the ascociation rule is capable to generate precise recommendations with confidence values 76.92%.

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