Semantic Annotation, Indexing, and Retrieval

  • Atanas Kiryakov
  • Borislav Popov
  • Damyan Ognyanoff
  • Dimitar Manov
  • Angel Kirilov
  • Miroslav Goranov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2870)

Abstract

The Semantic Web realization depends on the availability of critical mass of metadata for the web content, linked to formal knowledge about the world. This paper presents our vision about a holistic system allowing annotation, indexing, and retrieval of documents with respect to real-world entities. A system (called KIM), partially implementing this concept is shortly presented and used for evaluation and demonstration.

Our understanding is that a system for semantic annotation should be based upon specific knowledge about the world, rather than indifferent to any ontological commitments and general knowledge. To assure efficiency and reusability of the metadata we introduce a simplistic upper-level ontology which starts with some basic philosophic distinctions and goes down to the most popular entity types (people, companies, cities, etc.), thus providing many of the inter-domain common sense concepts and allowing easy domain-specific extensions. Based on the ontology, an extensive knowledge base of entities descriptions is maintained.

Semantically enhanced information extraction system providing automatic annotation with references to classes in the ontology and instances in the knowledge base is presented. Based on these annotations, we perform IR-like indexing and retrieval, further extended using the ontology and knowledge about the specific entities.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Atanas Kiryakov
    • 1
  • Borislav Popov
    • 1
  • Damyan Ognyanoff
    • 1
  • Dimitar Manov
    • 1
  • Angel Kirilov
    • 1
  • Miroslav Goranov
    • 1
  1. 1.Ontotext Lab, Sirma AI EOODSofiaBulgaria

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