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  • × author_ss:"Gnoli, C."
  • × year_i:[2020 TO 2030}
  1. Almeida, P. de; Gnoli, C.: Fiction in a phenomenon-based classification (2021) 0.01
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    Abstract
    In traditional classification, fictional works are indexed only by their form, genre, and language, while their subject content is believed to be irrelevant. However, recent research suggests that this may not be the best approach. We tested indexing of a small sample of selected fictional works by Integrative Levels Classification (ILC2), a freely faceted system based on phenomena instead of disciplines and considered the structure of the resulting classmarks. Issues in the process of subject analysis, such as selection of relevant vs. non-relevant themes and citation order of relevant ones, are identified and discussed. Some phenomena that are covered in scholarly literature can also be identified as relevant themes in fictional literature and expressed in classmarks. This can allow for hybrid search and retrieval systems covering both fiction and nonfiction, which will result in better leveraging of the knowledge contained in fictional works.
  2. Binding, C.; Gnoli, C.; Tudhope, D.: Migrating a complex classification scheme to the semantic web : expressing the Integrative Levels Classification using SKOS RDF (2021) 0.01
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    Abstract
    Purpose The Integrative Levels Classification (ILC) is a comprehensive "freely faceted" knowledge organization system not previously expressed as SKOS (Simple Knowledge Organization System). This paper reports and reflects on work converting the ILC to SKOS representation. Design/methodology/approach The design of the ILC representation and the various steps in the conversion to SKOS are described and located within the context of previous work considering the representation of complex classification schemes in SKOS. Various issues and trade-offs emerging from the conversion are discussed. The conversion implementation employed the STELETO transformation tool. Findings The ILC conversion captures some of the ILC facet structure by a limited extension beyond the SKOS standard. SPARQL examples illustrate how this extension could be used to create faceted, compound descriptors when indexing or cataloguing. Basic query patterns are provided that might underpin search systems. Possible routes for reducing complexity are discussed. Originality/value Complex classification schemes, such as the ILC, have features which are not straight forward to represent in SKOS and which extend beyond the functionality of the SKOS standard. The ILC's facet indicators are modelled as rdf:Property sub-hierarchies that accompany the SKOS RDF statements. The ILC's top-level fundamental facet relationships are modelled by extensions of the associative relationship - specialised sub-properties of skos:related. An approach for representing faceted compound descriptions in ILC and other faceted classification schemes is proposed.