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News
May 14, 2026
Resource Race and Green Transition: Three Unexpected Conclusions from Foresight Centres Research on Climate and Poverty
Beneath the surface of green energy—which most people associate with solar panels, electric vehicles, and reduced CO2 emissions—lies a complex web of geopolitical interests, international inequality, and resource constraints. Researchers from the Laboratory for Science and Technology Studies (LST) at the HSE ISSEK Foresight Centre have published a series of articles in leading international journals on hidden and overt conflicts surrounding critically important metals and minerals, as well as related processes in the energy sector.
May 13, 2026
Immersion in Second Language Environment Influences Bilinguals Perception of Emotions
Researchers at the Cognitive Health and Intelligence Centre at the HSE Institute for Cognitive Neuroscience have discovered how bilingual individuals process emotional words in their native (first) and non-native (second) languages. It was found that the link between word meaning and bodily sensations is weaker in a second language than in a first language. However, the more a person is immersed in a language environment, the smaller this difference becomes. The article has been published in Language, Cognition and Neuroscience.
May 12, 2026
‘Any Real-Economy Company Can Use Our Products
The HSE Centre for Financial Research and Data Analytics combines fundamental and applied work, including in areas unique to Russia such as the connection between sentiment in the media and social networks and financial markets. The HSE News Service spoke with the centre’s director, Professor Tamara Teplova, about its work.

 

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?

Topic Models Can Improve Domain Term Extraction

P. 684–687.
Elena Bolshakova, Natalia Loukachevitch, Nokel M.

Abstract. The paper describes the results of an experimental study of
topic models applied to the task of single-word term extraction. The
experiments encompass several probabilistic and non-probabilistic topic
models and demonstrate that topic information improves the quality of
term extraction, as well as NMF with KL-divergence minimization is the
best among the models under study.

Language: English
Text on another site
Keywords: кластеризацияclusteringTopic ModelsSingle-Word Term Extractionтематические моделиоднословные термины

In book

Proc. 35th European Conference on Information Retrieval (ECIR 2013): Advances in Information Retrieval
Vol. 7814. , Springer, 2013.
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