As people’s web usage is growing bigger, personalized support for web browsing is in great demand. Furthermore, the diversity of a user’s interests demands an appropriate methodology for profiling multiple domains of user interests. To comply with such demands, we propose one feasible design approach to support personalized web usage, in which a web user agent takes over the task of learning and profiling the multiplicity and the changeability of user interests. To evaluate the advantages of this approach, we have constructed a personalized web supporting system, in which an autonomous agent, namely the web guide agent, utilizes the information gathered by the web user agent for adaptation, e.g., selective retrieval and re-ranking of web links, and automatic delivery of specific web pages. Compared to other design alternatives, the proposed scheme is operationally simple, while producing acceptably reliable outcome.