Natural language processing

Semantic technologies for semantic applications. Part 2. Models of comparative text semantics

V. I. Gorodetsky^a, O. N. Tushkanova<sup>b

a</sup> TRA Robotics Ltd., St. Petersburg, Russia
^b St. Petersburg Institute for Informatics and Automation of RAS, St. Petersburg, Russia

Abstract: The both parts of the paper discuss the basic aspects of semantic computing, semantic technologies and semantic applications applied to NL-texts big data processing for knowledge extracting and decision-making. The basic components of the corresponding systems and technologies are reviewed, which include ontologies and semantic models of their use, semantic resources, and semantic component. The semantic resources contain knowledges about the words 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 main focus of this part is on numerical models of pairwise semantic similarity of NL-entities. These models are important for solving tasks of text semantic clustering and classification and their various applications. Various types of semantic relatedness and semantic similarity measures for NL-entities in the context of semantic computing tasks are discussed and compared. Problems that constrain the practical use of semantic technologies for the development of semantic applications are analyzed.

Keywords: semantic technology, semantic computing, semantic resource, comparative semantics, semantic relatedness, semantic similarity.

DOI: 10.14357/20718594190105

 English version: , 2020, 47:6, 365–373

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