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This article is cited in 2 scientific papers (total in 2 papers)
Natural language processing
Semantic technologies for semantic applications. Part 1. Basic components of semantic technologies
V. I. Gorodetskya, O. N. Tushkanovabc a TRA Robotics Ltd., St. Petersburg, Russia
b St. Petersburg Institute for Informatics and Automation of RAS, St. Petersburg, Russia
c Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
Abstract:
The paper discusses the basic aspects of modern understanding of semantic computations, semantic technologies and semantic applications in the field of artificial intelligence. The basic terminology used in the work is introduced, and concrete examples of semantic applications, including the industrial ones, are given. It is shown that the basic components of semantic technologies are ontologies and their semantic models, semantic resources and semantic component. The semantic resources contain knowledges about word semantics and means for refinement of this semantics. The semantic component of the technology is used to formally describe the meaning of NL-entities and numerically evaluate their pairwise semantic similarity. The available semantic resources are discussed and their comparative analysis is given. Information is given on the types of NL-entities (primitives), which are then practically used to build models of text meaning formal description in various semantic applications. The last components of the text semantics description constitute the content of the second part of this paper.
Keywords:
natural language semantics, semantic technology, semantic computing, semantic application, ontology, semantic resource.
Citation:
V. I. Gorodetsky, O. N. Tushkanova, “Semantic technologies for semantic applications. Part 1. Basic components of semantic technologies”, Artificial Intelligence and Decision Making, 2018, no. 4, 61–71; Scientific and Technical Information Processing, 46:5 (2019), 306–313
Linking options:
https://www.mathnet.ru/eng/iipr228 https://www.mathnet.ru/eng/iipr/y2018/i4/p61
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