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Acquisition of Soft Taxonomies for Intelligent Personal Hierarchies and the Soft Semantic Web

Martin, T ; Azvine, B

BT Technology Journal, 2003, Vol.21(4), pp.113-122 [Tạp chí có phản biện]

ISSN: 13583948

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  • Nhan đề:
    Acquisition of Soft Taxonomies for Intelligent Personal Hierarchies and the Soft Semantic Web
  • Tác giả: Martin, T ; Azvine, B
  • Chủ đề: Information Management ; Metadata ; Studies ; Mapping ; Systems Development ; Mathematical Models ; Experimental/Theoretical ; Software & Systems ; Management Science/Operations Research
  • Là 1 phần của: BT Technology Journal, 2003, Vol.21(4), pp.113-122
  • Mô tả: Metadata is a powerful tool in intelligent information management; however, it is not necessarily uniform, either in label or in content. One document's 'author' is another's 'creator'; 'John Smith', 'Smith, John' and 'J.Smith' all refer to the same individual but are syntactically different. Fusion (or intelligent integration) of information takes place in an environment where the data may be of varying quality, and some may be incomplete or inconsistent. Combining metadata (and the associated data) is not possible without knowing (or learning) the mappings between their ontologies. Such mappings are likely to be soft, i.e. approximate -- different sources arise from different designers with different world views. Soft computing is vital to tackle these problems. Frequently, data sources are organised implicitly, according to an internal ontology or taxonomy. Knowing this ontology or taxonomy is a necessary first step to using it in the fusion process. The work described in this paper extracts the implicit taxonomy and enables a user's interaction with the data (e.g. searching) to be expressed in their preferred terms rather than those used by the system.
  • Ngôn ngữ: English
  • Số nhận dạng: ISSN: 13583948

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