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Development of a Software for the Semantic Analysis of Social Media Content

  • Aleksey Filippov
  • Vadim MoshkinEmail author
  • Nadezhda Yarushkina
Conference paper
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 199)

Abstract

The paper presents a developed intelligent tool for Opinion Mining of social media. In addition, the article presents new algorithms to the hybridization of ontological analysis and methods of knowledge engineering with methods of nature language processing (NLP) for extracting the semantic and emotional component of semi-structured and unstructured text resources. These approaches will improve the efficiency of the analysis of social media content-specific data and fuzziness of natural language. Also the original algorithm for translating the RDF/OWL-ontology into a graphical knowledge base is proposed. In addition, the article presents an approach to the inference on the ontology repository. The approach based on translating the SWRL constructs into the elements of the Cypher language.

Keywords

Ontology Semantic analysis Social media Unstructured resources Graph knowledge base Inference SWRL OWL 

Notes

Acknowledgments

This study was supported by the Russian Foundation for Basic Research (Grants No. 18-47-730035, 18-47-732007, 18-37-00450, 18-47-732007).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Ulyanovsk State Technical UniversityUlyanovskRussia

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