Open AccessProceedings Article
Development of Linguistic Ontology on Natural Sciences and Technology
Boris V. Dobrov,Natalia V. Loukachevitch +1 more
- 01 May 2006
- pp 1077-1082
TL;DR: The paper describes the main principles of development and current state of Linguistic Ontology on Natural Sciences and Technology intended for information-retrieval tasks.
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Abstract: The paper describes the main principles of development and current state of Linguistic Ontology on Natural Sciences and Technology intended for information-retrieval tasks In the development of the ontology we combined three different methodologies: development of information-retrieval thesauri, development of wordnets, formal ontology research Combination of these methodologies allows us to develop large ontologies for broad domains
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Citations
RuThes Linguistic Ontology vs. Russian Wordnets
Natalia V. Loukachevitch,Boris V. Dobrov +1 more
- 01 Jan 2014
TL;DR: The structure and current state of RuThes – thesaurus of Russian language, constructed as a linguistic ontology is described and principles for inclusion of multiword expressions, types of relations, experiments and applications based onRuThes are described.
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OntoMath PRO Ontology: A Linked Data Hub for Mathematics
Olga Nevzorova,Nikita Zhiltsov,Alexander Kirillovich,Evgeny K. Lipachev +3 more
- 29 Sep 2014
TL;DR: In this article, the authors present an ontology of mathematical knowledge concepts that covers a wide range of the fields of mathematics and introduces a balanced representation between comprehensive and sensible models. And they argue that the ontology can be a core of future integration of math-aware data sets in the Web of Data and provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.
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•Posted Content
$OntoMath^{PRO}$ Ontology: A Linked Data Hub for Mathematics
TL;DR: It is argued that the ontology of mathematical knowledge concepts can be a core of future integration of math-aware data sets in the Web of Data and, therefore, provide mappings onto relevant datasets, such as DBpedia and ScienceWISE.
27
•Proceedings Article
Automatic Term Recognition Needs Multiple Evidence
Natalia V. Loukachevitch
- 01 May 2012
TL;DR: It is argued that the automatic term extraction procedure is an inherently multifactor process and the term extraction models needs to be based on multiple features including a specific type of a terminological resource under development.
References
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A practical course in terminology processing
Juan C. Sager
- 01 Jan 1990
TL;DR: This unique course has been developed on the basis of years of teaching experience and research at the University of Manchester Institute of Science and Technology (UMIST) and is particularly suitable for translation courses, freelance translators, technical writers, as well as for non-linguists who are confronted with terminology processing as part of their profession.
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Formal Ontology in Information Systems
Carola Eschenbach
- 01 Jan 2008
TL;DR: This ontology of risk-relevance (henceforth known as the ORR) is a tool for both data extraction professionals and risk-assessment professionals that allows new entries to be added easily when the need for additional information arises.
473
Natural Language Processing and Information Retrieval
TL;DR: Information retrieval addresses the problem of finding those documents whose content matches a user's request from among a large collection of documents by using statistical methods and natural language processing techniques.