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Making Explicit the Hidden Semantics of Hierarchical Classifications

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AI*IA 2003: Advances in Artificial Intelligence (AI*IA 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2829))

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Abstract

Hierarchical classifications are concept hierarchies used to organize large amounts of documents. File systems, products’ taxonomies for the market place and the directories provided by Web portals are common examples of hierarchical classifications. We propose a methodology for building a semantic interpretation of hierarchical classifications on the basis of the analysis of the taxonomic relations and the linguistic material they contain. We provide a formal semantics for hierarchical classifications and use it to interpret the implicit knowledge represented. Relevant phenomena addressed include the disambiguation of polysemous words, the semantics of multiwords, and the interpretation of coordinations. We report about experiments performed on the Web Directories of Google and Yahoo!.

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© 2003 Springer-Verlag Berlin Heidelberg

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Magnini, B., Serafini, L., Speranza, M. (2003). Making Explicit the Hidden Semantics of Hierarchical Classifications. In: Cappelli, A., Turini, F. (eds) AI*IA 2003: Advances in Artificial Intelligence. AI*IA 2003. Lecture Notes in Computer Science(), vol 2829. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39853-0_36

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  • DOI: https://doi.org/10.1007/978-3-540-39853-0_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20119-9

  • Online ISBN: 978-3-540-39853-0

  • eBook Packages: Springer Book Archive

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