Open AccessUsing semantic field model to create information search engines
Author(s) -
V E Sachkov,
Dmitry Zhukov,
Elena Andrianova
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 - 10.1088/1742-6596/1703/1/012051
Subject(s) - semantic search , computer science , search engine , field (mathematics) , semantic computing , information retrieval , semantic data model , semantic web , natural language understanding , search analytics , semantic technology , natural language , artificial intelligence , natural language processing , web search query , mathematics , pure mathematics
In the web infrastructure of information search, the use of semantic methods is considered to be a new round of the technology development. With the emergence of big data, a relevant issue is processing large amounts of data to extract valuable knowledge, especially for text files in natural language. Practice shows that traditional natural language search engines cannot always extract the necessary data from such data sets, as they do not take into account several subtle aspects of the language used in human speech. To solve this problem, the possibilities of using semantic search engines for text processing are being explored. This paper discusses the possible use of the semantic field model developed by the authors, to create a semantic search engine. Experiments have shown that using this model can improve the search accuracy. This model can be additionally used in creation of interactive dialogue systems.