<![CDATA[A product recommendation system is a necessity for e-commerce applications in order to recommend a series of products related to a product being viewed or previously purchased by the user of the e-commerce application. This article introduces STIMATA Rule Adviser, an interactive recommendation system developed using an association rule mining approach on data streams so that the recommended products are popularity-aware, meaning they are products that are always trending, currently popular, or products that are at risk because they are no longer selling well. This system is equipped with features that allow users to interact with the recommendation list. Users can choose the level of similarity and popularity of products in the recommendation list with the product they are currently viewing. User interactions with the provided recommendations can be visually monitored through the administrator's dashboard.]]>
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