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In this paper, we try to leverage a large-scale and multilingual knowledge base, Wikipedia, to help effectively analyze and organize Web information written in different languages. Based on the observation that one Wikipedia concept may be described by articles in different languages, we adapt existing topic modeling algorithm for mining multilingual topics from this knowledge base. The extracted 'universal' topics have multiple types of representations, with each type corresponding to one language. Accordingly, new documents of different languages can be represented in a space using a group of universal topics, which makes various multilingual Web applications feasible.