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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Multilingual Text Classification Using Ontologies
verfasst von : Gerard de Melo, Stefan Siersdorfer
Erschienen in: Advances in Information Retrieval
Verlag: Springer Berlin Heidelberg
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In this paper, we investigate strategies for automatically classifying documents in different languages thematically, geographically or according to other criteria. A novel linguistically motivated text representation scheme is presented that can be used with machine learning algorithms in order to learn classifications from pre-classified examples and then automatically classify documents that might be provided in entirely different languages. Our approach makes use of ontologies and lexical resources but goes beyond a simple mapping from terms to concepts by fully exploiting the external knowledge manifested in such resources and mapping to entire regions of concepts. For this, a graph traversal algorithm is used to explore related concepts that might be relevant. Extensive testing has shown that our methods lead to significant improvements compared to existing approaches.