An integrated framework for recommendation systems in e‐commerce

The Internet has become a popular medium for information exchange and knowledge delivery. Several traditional social activities have moved to the Internet, such as distance learning, tele‐medical system and. traditional buying and selling activities. Online merchants must know what users want, so providing recommendation services is an important strategy. Analyzes users’ on‐line behavior and interests, and recommends to them new or potential products. The analysis mechanism is based on the correlation among customers, product items, and product features. An algorithm is developed to classify users into groups and the recommendation is based on the classification. The system can help merchants to make suitable business decisions and provide personalized information to the customers. A generic mobile agent framework for e‐commerce applications is proposed. The aforementioned collaborative computing architecture for the recommendation system is based on the framework.