home > library > publications > knowledge representation, ontological engineering, and ...

schließen Subject Identifier für Knowledge Representation, Ontological Engineering, and Topic Maps
  • http://www.topicmapslab.de/publications/knowledge_representation_ontological_engineering_and_topic_maps

Knowledge Representation, Ontological Engineering, and Topic Maps

Book Chapter, veröffentlicht von Leo Obrst und Howard Liu am 01.07.2002

This chapter will discuss the explicit enabling of the representation of semantics in ontologies.

Consider the typical manner in which people currently use the Web browsers. They click to link to a document for which they’ve either searched, using simple keywords, or which is already indexed in the page they are viewing. The document is then displayed before them. They must then read the document and, using their own internalized conceptual model of the world and that document’s domain, interpret the meaning of the document. The knowledge in the document is not necessarily available to them: it may require extensive background information, long experience, or many years of formal education for users to understand what the document presents. For example, a retrieved document on the topic of interacting bosons in particle physics has knowledge that the average person cannot extract. The knowledge cannot be captured and transferred because the average person cannot interpret the words semantically, cannot decipher their intended meaning. Why? Because the person does not have a sufficiently rich conceptual model of that domain.

Today’s applications (such as keyword-based search engines) require the individual human user to be their semantic interpreter, that is, the user must figure out the knowledge contained in a document without any computer software interpretation of the meaning of that document. This chapter will discuss ways to remedy that situation. By explicit enabling the representation of semantics in ontologies and using these, tomorrow’s applications can assist the user by performing some of the semantic interpretation automatically.


Howard Liu

Keine Kontaktinformationen verfügbar. 


Howard ist Autor von Knowledge Representation,.. .


Follow us on Twitter


Topic Maps provides a proven means for data integration scaling to the
web, as well as a core technology for our highly flexible applications
with largely autogenerated frontend structures.

Stefan Kesberg
topicWorks Navigator
Topic Maps Lab auf der Cebit 2011

Graduate from the Topic Maps Lab