The enormous amount of information available over the Internet has forced users to face information overload while browsing the World Wide Web. Alongside with search engines, recommender systems and web personalization are seen as a remedy to this problem, since users are browsing the web according to their informational expectations while having a sort of implicit conceptual model in their mind. The latter is partially shared with other site visitors. In this paper we apply ontological modeling of anonymous ad-hoc web users' behavior to improve online user action prediction for web personalization via recommendations.