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Accurately identifying and profiling users is one of the primary challenges of many modern web applications. This paper presents an approach for user profiling that utilizes Fuzzy User Signatures combined with browser fingerprinting techniques. Our approach analyzes users' web domain visit frequencies and categories to determine their preferences and behaviors. Fuzzy User Signatures provide a condensed representation of user activities, enabling a framework for assessing user similarity. This method can significantly improve web navigation experiences by allowing for personalized content and product recommendations. The approach has been evaluated on a dataset comprising users' web activities combined with browser fingerprints, achieving overall good performances.