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Journal Neurocomputers №4 for 2016 г.
Article in number:
The method of text meaning analysis with semantic network containing fuzzy data
Keywords:
linguistics processor
natural language semantic analysis
linguistics variable
NLP
artifical neural net
Authors:
S.M. Salibekyan - Associate Professor, National Research University «Higher school of Economics», Moscow Institute of Electronics and Mathematics. E-mail: salibek@yandex.ru
S.B. Petrova - Magistrant, National Research University «Higher school of Economics»,
Moscow Institute of Electronics and Mathematics. E-mail: sv.halkina@gmail.ru
Abstract:
The paper describes the developed technique for extracting fuzzy data from a natural language text and for its analysis. The me-thod includes the principle of operation of the linguistic processor, the input data organization, the format of the generated data structure (semantic network with integrated descriptions of fuzzy data) and methods for information search. The analysis system is based on the object-attribute (OA) principle of the data and computing process organization. The fuzzy data are specified using the formalism of specially developed linguistic function (LF), which is an analogue of a linguistic variable. In the paper, attention is paid to the LF implementation by a neural network and to the method for comparing the output values of these LF during the information search in the semantic network.
Pages: 37-42
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