Three classes of documents, based on their data, circulate in the web: Unstructured documents (.Doc, .html, .pdf ...), semi-structured documents (.xml, .Owl ...) and structured documents (Tables database for example). A semi-structured document is organized around predefined tags or defined by its author.
However, many studies use a document classification by taking into account their textual content and underestimate their structure. We attempt in this paper to propose a representation of these semi-structured web documents based on weighted vectors allowing exploiting their content for a possible treatment. The weight of terms is calculated using: The normal frequency for a document, TF-IDF (Term Frequency - Inverse Document Frequency) and logic (Boolean) frequency for a set of documents. To assess and demonstrate the relevance of our proposed approach, we will realize several experiments on different corpus.