The rapid evolution of the Internet from a general information space to an electronic market space provides the users with the possibility to navigate among thousands of Web sites for comparing products and merchants, for making their purchases or for obtaining some desired services. However, from the user's viewpoint, such a navigation often requires an high cost in terms of time to spend on the Web to perform a satisfying comparison of the various alternatives. From the supplier's viewpoint, it is needed to propose products in a suitable way to customers, taking into account the typology of each customer, her/his preferences, habits, etc. In this context, generally denoted as Business-to-Customer (B2C) e-commerce, the use of software agents as mediators in e-commerce activities seems to be particularly promising. In this paper, we describe and analyze the various roles agents have assumed in B2C e-commerce applications. Furthermore, we propose a Consumer Buying Behaviour model, called E 2-CBB, that considers new emergent issues, as the capability to solve semantic heterogeneity, and the adaptive presentations of Web stores. By using such a model, we classify and compare a number of agent-based approaches for managing B2C e-commerce, proposed in the literature in the last ten years.
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