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Published since 1998
ISSN 1562-5419
16+
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Building Subject Domain Ontology on the Base of a Logical Data Mod

Alexander M. Gusenkov, Naille R. Bukharaev, Evgeny V. Biryaltsev
390-417
Abstract: The technology of automated construction of the subject domain ontology, based on information extracted from the comments of the TATNEFT oil company relational databases, is considered. The technology is based on building a converter (compiler) translating the logical data model of Epicenter Petrotechnical Open Software Corporation (POSC), presented in the form of ER diagrams and a set of the EXPRESS object-oriented language descriptions, into the OWL ontology description language, recommended by the W3C consortium. The basic syntactic and semantic aspects of the transformation are described.
Keywords: subject domain ontology, relational databases, POSC, OWL.

Visualization tools for co-author networks and citation networks of large scientific portals

З.В. Апанович, П.С. Винокуров
Abstract: Due to the fast development of Semantic Web and its new branch of Linked Open Data, large amounts of structured information on various scientific areas become available. Digital libraries, information systems and portals based on ontologies are the most reliable sources of this information that need careful investigation in order to optimize science management. A generally accepted way to facilitate understanding of such large and complex data sets is graph visualization. This paper is devoted to newly developed visualization algorithms of co-authorship and citation networks extracted from information portals and digital libraries of the Linked Open Data cloud.
Keywords: scientific portal, ontology, content, information visualization, layered graph drawing, citation networks, modularity, Open Linked Data.

Sentiment classification of reviews and twitter posts based on dictionaries

Елена Викторовна Тутубалина, Владимир Владимирович Иванов, Мария Загулова, Никита Мингазов, Ильсеяр Алимова, Валентин Малых
138-162
Abstract:

Sentiment analysis and opinion mining technologies are growing fast. This is mostly due to a rapid grow of the data sources consisting a vast amount of user opinions and reviews on a wide set of topics. In this paper we describe methods for sentiment analysis of reviews and short messages (tweets), as well as evaluation of results obtained during SentiRuEval-2015.

Keywords: information extraction, sentiment analysis, text classification, supervised learning.

Digital Technologies of the Future for Scientific Research in Geology

Vera Viktorovna Naumova, Michail Ivanovich Patuk, Alexander Sergeevich Eremenko, Aleksey Andreevich Zagumennov, Vitaliy Sergeevich Eremenko
788-805
Abstract:

The article discusses technologies that can radically change the development of many areas at once: artificial intelligence, quantum technologies, big data, wireless communication technologies, distributed registry systems. The authors consider a number of promising technologies of the near future that currently have prospects for application in Earth sciences. The review of the application of these technologies to solve various geological problems, including the results obtained by the authors, is carried out.

Keywords: artificial intelligence, numerical tools, virtual assistants, intelligent agents, numerical technologies of the future in geology.
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Russian Digital Libraries Journal

ISSN 1562-5419

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