An ontology is a computer-readable conceptualization of a domain, which thus formally represents the “knowledge” about a domain in a structured and computer readable way and is defined through:

 

• A hierarchy of object classes (“concepts”, “types”), sub-classes and concrete manifestations of those concepts (“instances”). The ontological hierarchy is expressed in an “is a” Relationship: For two concepts A and B, A may be a “concept” or “class” (e.g. Land Vehicles) and B may be a sub-class of A (e.g. Hybrid Cars), then B “is an” A. Then Toyota Prius “Is an” instance of Hybrid Cars. Another “concept” may be “Engine Type” with instances of “hybrid engine”, “benzene engine”, “diesel engine”. The hierarchy also applies to locations and enables links between places: Penn Station ~ Manhatten ~ New York City ~ United States. 

• Semantic properties (attributes and relationships) – each attribute may hold a value that points to a concept or instance in the ontology (e.g. the attribute of “Engine Type” in the instances of Hybrid Cars, inherited by the instance of Toyota Prius will be “hybrid engine” which is an instance of the concept “Engine Type” and other attributes that define the Toyota Prius may be “Manufacturer” (=Toyota), and Country of Origin (=Japan).

 

The relationship between concepts and instances are expressed when:

• There is a proximity between them in their place in the hierarchy of the ontology - if instance A and instance B have the same parent concept or grandparent concept.

• They contain attributes that are close to each other in the ontology, for example, if instance A and instance B have the same attributes or related attributes, they are relate

 

 

The utility of ontologies is manifest in a polyglot and multi-domain world in which mere words have multiple meanings (polysemy) and in order to disambiguate them, we must define them clearly.

Ontologies, therefore, are an “Esperanto” of cyber communication. A simile that defines them well was offered by Warren Weaver in his efforts to develop machine translation:

"Think, by analogy, of individuals living in a series of tall closed towers, all erected over a common foundation… When they try to communicate with one another, they shout back and forth, each from his own closed tower. It is difficult to make the sound penetrate even the nearest towers, and communication proceeds very poorly indeed. But, when an individual goes down his tower, he finds himself in a great open basement, common to all the towers. Here he establishes easy and useful communication with the persons who have also descended from their towers".

 

In the IntuView technology, the ontology is part of a vast knowledge base (KB). The Knowledge Base consists of:

• Ontology packages -  The ontology is domain-specific and language-independent. It is written in the English-based annotation. The ontology is connected to lexicons of all the supported languages.

• Lexicons packages – these are language-specific (i.e. a lexicon for each language). A lexicon is a set of lexemes of a given language (e.g. English, Arabic etc.) that could appear in a text of that language. Lexemes in the text are linked to ontological instances. Each language has lexicon packages that correspond to the ontology packages. A lexicon entry may have morphological and syntactic rules that determine under what conditions, it “means” or is mapped to a certain ontological instance (e.g. ship (noun) is mapped to “sea-going vessel”, ship (verb) is mapped to “transport”). A lexical entry in one language may be mapped to a number of ontological instances, whereas its “translation” in another language may have a more restricted set of semantic meanings.

• “Sources” are full documents in which each parsed element (article, verse) is linked to one or more ontological instances.

• The Rule Base is a set of algorithms that define conditions for linking a lexeme or set of lexemes to ontology concepts.