Extracting Nomenclature Names from Scientific and Technical Texts in Russian and English

This article proposes a method of extracting nomenclature names in Russian and English from scientific and technical texts according to their structural models. An analysis of their structural and semantic features is made and used as the basis for creating models of nomenclature names in Russian and English. A method of automatically extracting nomenclature names from scientific and technical texts in English and Russian is proposed. The study results can be used in developing various systems of processing scientific and technical texts, marking up special corpora, collecting linguistic material for the creation of terminology dictionaries and databases by considering a larger number of models of special vocabulary and using methods of processing scientific and technical texts in Russian and English.

Authors

Institutions

Publication Details

Journal
Scientific and Technical Information Processing
Published
2025-12-01
DOI
https://doi.org/10.3103/s0147688225700534
Primary Topic
linguistics and terminology studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Extracting Nomenclature Names from Scientific and Technical Texts in Russian and English

Iu. I. Butenko
Scientific and Technical Information Processing
linguistics and terminology studies
article

Extracting Nomenclature Names from Scientific and Technical Texts in Russian and English

Iu. I. Butenko
article en

Abstract

This article proposes a method of extracting nomenclature names in Russian and English from scientific and technical texts according to their structural models. An analysis of their structural and semantic features is made and used as the basis for creating models of nomenclature names in Russian and English. A method of automatically extracting nomenclature names from scientific and technical texts in English and Russian is proposed. The study results can be used in developing various systems of processing scientific and technical texts, marking up special corpora, collecting linguistic material for the creation of terminology dictionaries and databases by considering a larger number of models of special vocabulary and using methods of processing scientific and technical texts in Russian and English.

Scientific and Technical Information ProcessingVol. 52(6)
Bauman Moscow State Technical University (RU)
Quality Education
Openalex Percentile: Top 9%
linguistics and terminology studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.