DETECTION OF COMPLEX SEMANTICS FROM UNSTRUCTURED DATA USING NLP & CONVOLUTION NEURAL NETWORK TECHNIQUE
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DETECTION OF COMPLEX SEMANTICS FROM UNSTRUCTURED DATA USING NLP & CONVOLUTION NEURAL NETWORK TECHNIQUE
1Shankarayya Shastri, 2Dr.Veeragangadharaswamy T.M
1Research Scholar, Dept. of CSE, RYMCE, Ballari -583104
2Professor, Dept. of CSE, RYMCE, Ballari -583104
ABSTRACT: The majority of data on computers nowadays still takes the form of unstructured text. The inherent ambiguity of natural language makes it incredibly difficult but also highly profitable to find hidden information or comprehend complex semantics in unstructured text. In this paper, we present combination of Natural Language Processing (NLP) and Convolution Neural Network (CNN) hybrid architecture for detection of complex semantics from unstructured data that enables different users to make understand formal semantic knowledge to be extracted from an unstructured text corpus.
Keywords— Convolution Neural Network, Natural Language Processing, Controlled Natural Language, Text Mining, Information Extraction.
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