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Semantic Technologies: A Computational Paradigm for Making Sense of Qualitative Meaning Structures

Abstract

The World Wide Web has become the largest container of human-generated knowledge but the current computational infrastructure suffers from inadequate means to cope with the meaning captured in its interlinked documents. Semantic technologies hold the promise to help unlock this information computationally. This novel paradigm for the emerging Semantic Web is characterized by its focus on qualitative, from the perspective of computers un(der)structured, data, with the goal to ‘understand’ Web documents at the content level. In this contribution, fundamental methodological building blocks of semantic technologies are introduced, namely terms (symbolic representations of very broadly conceived ‘things’ in the real world), relations between terms (assertions about states of the world), and formal means to reason over relations (i.e. to generate new, inferentially derived assertions about states of the world as licensed by rules). We also discuss briefly the current status and future prospects of semantic technologies in the Web.

Keywords

  • Natural Language
  • Inference Rule
  • Semantic Relation
  • Description Logic
  • Predicate Symbol

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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Notes

  1. 1.

    http://blast.ncbi.nlm.nih.gov/Blast.cgi

  2. 2.

    http://www.w3.org/2001/sw/

  3. 3.

    Seth Grimes discusses the myth of the 80% rule (80% of the data on the Web are stipulated to be un- or semi-structured, whereas only the remaining 20% are structured and thus easily interpretable by machines) that has evolved from several hard to track sources (mostly observations made by IT companies, e.g. database, network and storage suppliers); see http://clarabridge.com/default.aspx?tabid=137&ModuleID=635&ArticleID=551. A summary of the arguments related to the proliferation of unstructured data is contained in [41].

  4. 4.

    One of the most remarkable exceptions to this observation is due to the introduction of the logic programming paradigm around 1980 and Prolog, its primary programming language representative, which was based on Horn clause logic [13].

  5. 5.

    We distinguish terminological semantic relations from assertional semantic relations, the latter covering the multitude of empirical assertions such as interacts-with, is-effective-for, is-mother-of, and is-located-in.

  6. 6.

    http://wordnet.princeton.edu/

  7. 7.

    http://semanticnetwork.nlm.nih.gov/

  8. 8.

    http://sig.biostr.washington.edu/projects/fm/

  9. 9.

    http://www.geneontology.org/

  10. 10.

    This number is based on the lexical population statistics of WordNet, the most comprehensive lexical database for the English language.

  11. 11.

    Formally speaking, we here outline a system which is usually referred to as typed first-order logic (Fol; see, e.g. [18]). Throughout the discussion, we avoid going into low-level details of Fol, in particular, in what concerns the use of quantifiers.

  12. 12.

    http://www.nlm.nih.gov/research/umls/

  13. 13.

    http://www.obofoundry.org/

  14. 14.

    http://bioportal.bioontology.org/

  15. 15.

    http://agclass.nal.usda.gov/

  16. 16.

    http://www.loc.gov/lexico/servlet/lexico/liv/brsearch.html?usr=pub-13:0&op=frames&db=GLIN

  17. 17.

    http://www.getty.edu/research/tools/vocabularies/aat/index.html

  18. 18.

    http://www.isi.edu/natural-language/resources/sensus.html

  19. 19.

    http://www.cyc.com/

  20. 20.

    http://wordnet.princeton.edu/

  21. 21.

    https://framenet.icsi.berkeley.edu/fndrupal/

  22. 22.

    http://www.cs.man.ac.uk/~ezolin/dl/

  23. 23.

    http://www.w3.org/RDF/

  24. 24.

    http://www.w3.org/wiki/LargeTripleStores

  25. 25.

    http://www.w3.org/2001/sw/wiki/SKOS

  26. 26.

    http://www.w3.org/TR/rdf-schema/

  27. 27.

    http://trac.biostr.washington.edu/trac/wiki/FMAInOWL

  28. 28.

    http://ncicb.nci.nih.gov/download/evsportal.jsp

  29. 29.

    http://www.geneontology.org/GO.format.shtm

  30. 30.

    http://obofoundry.org/ro/

  31. 31.

    http://www.w3.org/wiki/SemanticWebArchitecture

  32. 32.

    http://www.w3.org/standards/semanticweb/data

  33. 33.

    https://www.mturk.com/mturk/welcome

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Hahn, U. (2013). Semantic Technologies: A Computational Paradigm for Making Sense of Qualitative Meaning Structures. In: Küppers, BO., Hahn, U., Artmann, S. (eds) Evolution of Semantic Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34997-3_8

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  • DOI: https://doi.org/10.1007/978-3-642-34997-3_8

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