Exploiting Client Logs to Support the Construction of Adaptive e-Commerce Applications

An essential feature of successful e-commerce applications is the ability to provide the right content at the right time for the user. Therefore, personalization techniques have been exploited to build adaptive applications in which the user interfaces change according to the user needs and preferences. In this work, we advocate that it is possible to achieve personalization by analyzing the behavior of the user when browsing an e-commerce application. In order to prove our hypothesis, we built a toolkit that allows the automatic gathering and analysis of client logs in real-time. Moreover, our solution provides a Web service that exposes the analysis outcome also in real-time, thus allowing the client application to adapt on-the fly according to the results provided by the toolkit. This paper presents a case study that demonstrate the effectiveness of our approach to support the construction of adaptive e-commerce applications.