Sentence Recognition Using Hopfield Neural Network
Communication in natural languages between computational
systems and humans is an area that has attracted researchers for
long. This type of communication can have wide ramification as
such a system could find wide usage in several areas. Web-
Browsing via input given as textual commands/sentences in
natural languages is one such area. However, the enormous
amount of input that could be given in natural languages present
a huge challenge for machine learning of systems which are
required to recognize sentences having similar meaning but
different lexico-grammatical structures. In this paper, we
describe how a binary recurring neural network can be used to
sufficiently solve this problem for English. The system uses the
Hopfield Neural Network to recognize the meaning of text using
training files with limited dictionary. Detailed analysis and
evaluation show that the system correctly recognizes/classifies
approximately 92.2% of the input sentences according to their
meaning.
Keywords: Artificial Neural Network, Expert Systems, Machine
learning, Natural Language, Sentence Recognition
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