Open AccessA neural network algorithm for extracting pharmacological information from russian-language internet reviews on drugs
Author(s) -
Alexander Sboev,
Sanna Sboeva,
Artem Gryaznov,
A. V. Evteeva,
Roman Rybka,
M. S. Silin
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1686/1/012037
Subject(s) - computer science , task (project management) , artificial intelligence , basis (linear algebra) , context (archaeology) , conditional random field , the internet , convolution (computer science) , artificial neural network , natural language processing , machine learning , pattern recognition (psychology) , mathematics , paleontology , geometry , management , world wide web , economics , biology
The paper presents a neural network algorithm for analyzing online user reviews of drugs. The algorithm was validated on specially prepared and annotated corpora. The basis of the algorithm is a neural network model combining convolution and recurrent layers, context-dependent vector representations of words, conditional random fields and additional features of words obtained from different dictionaries. The proposed model showed accuracies comparable to the state-of-the-art results for this task on the corpora for other languages.