A semantic net (or semantic network) is a knowledge representation technique used for propositional information. So it is also called a propositional net. Semantic nets convey meaning. Semantic nets are two dimensianal representations of knowledge. Mathematically a semantic net can be defined as a labeled diercted graph.
Semantic nets consist of nodes, links (edges) and link labels. In the semantic network diagram, nodes appear as circles or ellipses or rectangles to represent objects such as physical objects, concepts or situations. Links appear as arrows to express the relationships between objects, and link labels specify particular relations. Relationships provide the basic structure for organizing knowledge. The objects and relations involved need not be so concrete. As nodes are associated with other nodes semantic nets are also referred to as assiciative nets.
In the above figure all the objects are within ovals and connected using labelled arcs. Note that there is a link between Jill and FemalePersons with label MemberOf. Simlarly there is a MemberOf link between Jack andMalePersons and SisterOf link between Jill and Jack. The MemberOf link between Jill and FemalePersons indicates that Jill belongs to the category of female persons.
Inheritance Reasoning
Unless there is a specific evidence to the contrary, it is assumed that all members of a class (category) will inherit all the properties of their superclassess. So semantic network allows us to perform inheritance reasoning. For example Jill inherits the property of having two legs as she belongs to the category of FemalePersons which in turn belongs to the category of Persons which has a boxed Legs link with value 2. Semantic nets allows multiple inheritance. So an object can belong to more than one category and a category can be a subset of more than one another category.
Inverse links
Semantic network allows a common form of inference known as inverse links. For example we can have a HasSister link which is the inverse of SisterOflink.The inverse links make the job of inference algorithms much easier to answer queries such as who the sister of Jack is. On discovering that HasSisteris the inverse of SisterOf the inference algorithm can follow that link HasSister from Jack to Jill and answer the query.
Diasdvantage of Semantic Nets
One of the drawbacks of semantic network is that the links between the objects represent only binary relations. For example, the sentence Run(ChennaiExpress, Chennai,Bangalore,Today) cannot be asserted directly.
There is no standard definition of link names.
Advantages of Semantic Nets
Semantic nets have the ability to represent default values for categories. In the above figure Jack has one leg while he is a person and all persons have two legs. So persons have two legs has only default status which can be overridden by a specific value.
Semantic nets convey some meaning in a transparent manner.
Semantic nets are simple and easy to understand.
Semantic nets are easy to translate into PROLOG.
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