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This paper presents a novel approach for text classification on biomedical literature, involving the use of information extracted from related web resources. Our method creates a representation of an article based on information extracted from public online databases, that is afterwards used by traditional statistical text classification algorithms. We validated this approach by implementing the proposed method, and testing it on the KDD2002 Cup challenge: bio-text task. Results show that our approach of searching for additional data on online databases can effectively improve efficiency on text classification systems for biomedical literature