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Ontologies pp 19-46 | Cite as

Application Area Knowledge Management

  • Dieter Fensel

Abstract

In the meantime, large Companies have intranets with several million pages. Finding, creating and maintaining information is a rather difficult problem in this weakly structured representation media. On the other hand, the competitiveness of companies active in areas with a high change rate depends heavily on how they maintain and access their knowledge. Therefore, Knowledge Management deals with acquiring, maintaining, and accessing knowledge of an organization. In the following, I will discuss some of the pitfalls of current techniques and will then show some existing approaches that make use of ontologies for providing much stronger support.1

Keywords

Resource Description Framework Inference Engine Query Interface Query Engine Query Answering 
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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Reference

  1. 1.
    Actually, I only discuss a small number of prototypical approaches. There are many valuable and interesting ontology-based approaches in this area which I do not discuss: (ONTO)Google Scholar
  2. 2.
    Agent [Arpírez et al., 1998], ONTOSEEK [Guarino et al., 1999], PlanetOnto [Domingue and Motta, in press], TREVI [Meersman, 1999], and FindUR [McGuinness, 1998], now deployed as SmartSearch on ATandT’s worldnet service.Google Scholar
  3. 6.
    This limitations become rather comical as in the meantime AltaVista retrieved a description of Ontobroker (see the following subsection) as result of the query feather+research because this query was used in on-line available publications dealing with Ontobroker (see Figure 6).Google Scholar
  4. 7.
    Compare this with databases and SQL, where a user can make precise queries leading to precise answers.Google Scholar
  5. 8.
    SHOE (cf. [Luke et al., 1996], [Luke et al. 1997]) introduced the idea of using ontologies for annotating web sources. There are two main differences to Ontobroker. First, the annotation language is not used to annotate existing information in web pages, but to add additional information and annotate them. That is, in SHOE information must be repeated and this redundancy may cause significant maintenance problems. For example, an affiliation must once be provided as a text string rendered by the browser and a second time as annotated meta-information. In this respect, SHOE is close to meta-tags in HTML. Ontobroker uses the annotations to directly add semantics to textual information that is also rendered by a browser. A second difference is the use of inference techniques and axioms to infer additional knowledge. SHOE relies only on database techniques. Therefore, no further inference service is provided. Ontobroker uses an inference engine to answer queries. Therefore, it can make use of rules that provide additional information.Google Scholar
  6. 9.
    Syntactical rules that ensure that the subset of minimal model that has to be computed remains finite are described in [Fensel et al., 1998b].Google Scholar
  7. 14.
    In terms of the database community On2broker is a kind of data warehouse for data in the Web. Queries are not run on the sources to which On2broker provides access, but on a database into which the source content has been extracted. In addition to the facts that can be found explicitly in the sources, the system also applies rules to derive additional information.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Dieter Fensel
    • 1
  1. 1.Division of Mathematics and Computer ScienceFrije Universiteit AmsterdamAmsterdamThe Netherlands

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