Web personalizationcan be defined as any set of actions that can tailor the Web experience to a particular user or set of users. The experience can be something as casualas browsinga Web site oras (economically)significantas tradingsk or purchasing a car. The actions can range from simply making the presentation more pleasing to anticipating the needs of a user and providing customized and relevant information. To achieve effective personalization, organizations must rely on all available data, including the usage and click-stream data (refining user behavior), the site content, the site structure, domain knowledge, user demographics and profiles. In addition, efficient and intelligent techniques are needed to mine these data for actionable knowledge, and to effectively use the discovered knowledge to enhance the users’ Web experience. These techniques must address important challenges emanating from the size and the heteroge- ity of the data, and the dynamic nature of user interactions with the Web. E-commerce and Web information systems are rich sources of difficult pr- lems and challenges for AI researchers. These challenges include the scalability of the personalization solutions, data integration, and successful integration of techniques from machine learning, information retrievaland—ltering, databases, agent architectures, knowledge representation, data mining, text mining, stat- tics, user modelling and human–computer interaction. Throughout the history of the Web, AI has continued to play an essential role in the development of Web-based information systems, and now it is believed that personalization will prove to be the “killer-app” for AI.