Sentence Recognition Using Hopfield Neural Network
نویسندگان
چکیده
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. WebBrowsing 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
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