<![CDATA[E-commerce with a system of recommendations based collaborative filtering is designed to help stores in develop businesses is global. In this application will be provided recommendations in order to system to make it easier for the consumers in to look for intended products, saw a products and sold based on the categories. To make sure consumers in choosing the product and the production of application by implementing recommendations. Where the system would recommend a intended products can also can refine based on the category. The recommendations in this system in a collaborative filtering. The value rating by consumers collected in a matrix of consumers and products. In counting to get a resemblance and applied also method adjust cosine-based similarity and to value his prediction own use weighted sum. Recommended products system to consumers by gathering information about histori purchase.When consumers choose town living, will products histori recommended based on the purchase by the area.Therefore reduced purchasing power of buyers will increase it is presented products in accordance with era development.]]>
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