Semantic annotation of text documents based on hierarchical radial basis neural network

Authors

  • Евгений Владимирович Бодянский Кафедра искусственного интеллекта Харьковский национальный университет радиоэлектроники, Ukraine
  • Ольга Васильевна Шубкина Кафедра искусственного интеллекта Харьковский национальный университет радиоэлектроники, Ukraine

DOI:

https://doi.org/10.15587/1729-4061.2010.3262

Keywords:

semantic annotation, radial basis function neural network, multi-layered architecture

Abstract

The hierarchical radial basis function neural network with a multi-layered architecture is proposed. This neural network is used for extracting knowledge from textual sources with the maximum number of relevant attributes for each object and assigns it to the selected class of ontology.

Author Biographies

Евгений Владимирович Бодянский, Кафедра искусственного интеллекта Харьковский национальный университет радиоэлектроники

Доктор технических наук, профессор

Ольга Васильевна Шубкина, Кафедра искусственного интеллекта Харьковский национальный университет радиоэлектроники

Аспирант

References

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Published

2010-11-10

How to Cite

Бодянский, Е. В., & Шубкина, О. В. (2010). Semantic annotation of text documents based on hierarchical radial basis neural network. Eastern-European Journal of Enterprise Technologies, 6(3(48), 72–77. https://doi.org/10.15587/1729-4061.2010.3262

Issue

Vol. 6 No. 3(48) (2010): Control systems

Section

Control systems

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Copyright (c) 2014 Евгений Владимирович Бодянский, Ольга Васильевна Шубкина

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