It is a method to represent the natural languages. It is based on applications of directed graphs and finite state automata.

**TRANSITION NETWORK**

It is a method to represent the natural languages. It is based on
applications of directed graphs and finite

state automata. The transition network can be constructed by the help of
some inputs, states and outputs. A transition network may consist of some states
or nodes, some labeled arcs from one state to the next state through which it
will move. The arc represents the rule or some conditions upon which the
transition is made from one state to another state. For example, a transition
network is used to recognize a sentence consisting of an article, a noun, an
auxiliary, a verb, an article, a noun would be represented by the transition
network as follows.

The transition from N_{1} to N_{2} will be made if an article is the first input symbol. If successful,
state N_{2} is entered. The transition from N_{2} to N_{3} can be made if a noun is found next. If successful, state N_{3} is entered. The transition from
N_{3} to N_{4} can be made if an auxiliary is found and so on. Suppose consider a
sentence “A boy is eating a banana”. So if the sent ence is parsed in the above
transition network then, first ‘A’ is an article. So successful transition t o
the node N_{1} to N_{2}. Then boy is a noun (so N_{2} to N_{3}), “is” is an auxiliary (N_{5} to N_{6}) and finally “banana” is a noun (N _{6} to N_{7}) is done successfully. So the above sentence is successfully parsed in
the transition network.

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Artificial Intelligence : Transition Network |

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