Abstract
Natural language descriptors used for categorizations are present from folksonomies to ontologies. While some descriptors are composed of simple expressions, other descriptors have complex compositional patterns (e.g. ‘French Senators Of The Second Empire’, ‘Churches Destroyed In The Great Fire Of London And Not Rebuilt’). As conceptual models get more complex and decentralized, more content is transferred to unstructured natural language descriptors, increasing the terminological variation, reducing the conceptual integration and the structure level of the model. This work describes a representation for complex natural language category descriptors (NLCDs). In the representation, complex categories are decomposed into a graph of primitive concepts, supporting their interlinking and semantic interpretation. A category extractor is built and the quality of its extraction under the proposed representation model is evaluated.
Keywords
- Resource Description Framework
- Word Sense Disambiguation
- Inverse Document Frequency
- Lexical Category
- Natural Language Descriptor
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Freitas, A., Vieira, R., Curry, E., Carvalho, D., da Silva, J.C.P. (2014). On the Semantic Representation and Extraction of Complex Category Descriptors. In: Métais, E., Roche, M., Teisseire, M. (eds) Natural Language Processing and Information Systems. NLDB 2014. Lecture Notes in Computer Science, vol 8455. Springer, Cham. https://doi.org/10.1007/978-3-319-07983-7_6
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DOI: https://doi.org/10.1007/978-3-319-07983-7_6
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07982-0
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