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

close subject identifiers for 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, was published by Leo Obrst and Howard Liu at 2002-07-01

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

No contact information available. 


Howard is author of Knowledge Representation,.. .


Follow us on Twitter


Topic Maps is the only formal semantic model which is optimized for humans, not for computers. Applications and web portals based on Topic Maps are easy to use, without limitations for flexibility and creativity.

Benjamin Bock
Ruby Topic Maps
Topic Maps Lab auf der Cebit 2011

Graduate from the Topic Maps Lab