WHAT IS SEMANTIC NET? GIVE EXAMPLE.

SEMANTIC NET

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. They are two dimensional representations of knowledge. Mathematically a semantic net can be defined as a labeled directed graph.

The main idea behind semantic nets is that the meaning of a concept comes from the ways in which it is connected to other concepts. In semantic net, information is represented as a set of nodes connected to each other by set of labeled arcs, which represent relationships among the nodes.

INHERITANCE REASONING

Semantic net allows us to perform inheritance reasoning as all members of a class will inherit all the properties of superclass .We could use inheritance to derive the additional relation. Semantic nets allow 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

It allows a common form of inference known as inverse links. For example we can have a HasMother link which is the inverse of MotherOf link. The inverse links make the job of inference algorithms much easier to answer queries such as who the mother of John is. On discovering that HasMother is the inverse of MotherOf the inference algorithm can follow that link HasMother from John to Gavy and answer the query.

ADVANTAGES

· Semantic nets have the ability to represent default values for categories. In the above figure John 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.

· They convey some meaning in a transparent manner.

· They nets are simple and easy to understand.

· They are easy to translate into PROLOG.

DISADVANTAGES

· One of the drawbacks of semantic network is that the links between the objects represent only binary relations. For example, the sentence Run(RajdhaniExpress, Chandigarh,delhi,Tomorrow) cannot be asserted directly.

· There is no standard definition of link names.

EXAMPLE

· Tom is an instance of dog.

· Tom caught a cat

· Tom is owned by rashan.

· Tom is brown in colour.

· Dogs like bones.

· The dog sat on the mat.

· A dog is a mammal.

· A cat is an instance animal

· All mammals are animals.

· Mammals have fur.

This network contains examples of isa relation, as well as some other, more domain-specific relations like sat_on, like, caught, is_coloured, is_owned_by. In this network, we could use inheritance to derive the additional relation

sat_on (Tom,Mat)