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News
October 14, 2026
At HSE University–St Petersburg, Experts Discuss How AI Changes Tourist Routes and Cultural Heritage
Neural networks are no longer simple travel assistants; now they decide what to include on the route and what to skip. Artificial intelligence changes how people perceive a place and shapes the image of tourist centres. At the II International Scientific and Practical Conference ’Information Technologies in the Preservation and Promotion of Cultural Heritage,’ researchers discussed who controls algorithmic solutions and in what ways, and whether authentic traditions get lost in them.
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.

 

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Proceedings of Third Workshop "Computational linguistics and language science"

Issue 4. Manchester : EasyChair, 2019.
Wohlgenannt G., von Waldenfels R., Toldova S., Rakhilina E. V., Lyashevskaya O., Loukachevitch N. V., Artemova E.

The EPiC Series in Language and Linguistics publishes high quality collections of papers in language, linguistics and related areas.

Chapters
Automatic morphological analysis on the material of Russian social media texts
Fenogenova A., Kazorin V., Karpov I. et al., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019. P. 11–17.
Automatic morphological analysis is one of the fundamental and significant tasks of NLP (Natural Language Processing). Due to special features of Internet texts, as they can be both normative texts (news, fiction, nonfiction) and less formal texts (such as blogs and texts from social networks), the morphological tagging has become non-trivial and an actual task. ...
Added: October 5, 2018
Amateur Prose On The Web: Verb Construction As A Feature Of Genre Classification
Builova N., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019.
In our research we studied the dependency structure of the text genre love stories, detective stories, science fiction and fantasy). The novel characteristics (such syntactic attributes as verb constructions and construction of a specific cumulative threshold) which can be additional machine learning parameters were identified. We conducted experiment with novel features and showed that these ...
Added: December 11, 2018
Lemmatisation for under-resourced languages with sequence-to-sequence learning: A case of Early Irish
Dereza O., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019. P. 113–124.
Lemmatisation, which is one of the most important stages of text preprocessing, consists in grouping the inflected forms of a word together so they can be analysed as a single item. This task is often considered solved for most modern languages irregardless of their morphological type, but the situation is dramatically different for ancient languages. Rich inflectional system and ...
Added: December 12, 2018
Genre Classification Problem: in Pursuit of Systematics on a Big Webcorpus
Shavrina T., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019. P. 70–83.
This article is devoted to the problem of defining a genre in computer linguistics and searching for parameters that could formalize the concept of a genre. All kinds of existing typologies of genres rely on different types of features, whereas in the practice of NLP, any modern applications are adapted to learning on big data, ...
Added: September 9, 2019
Defining discourse formulae: computational approach
Gerasimenko Ekaterina, Puzhaeva Svetlana, Zakharova Elena et al., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019. P. 61–69.
In this paper, we address the problem of automatic extraction of discourse formulae. By discourse formulae (DF) we mean a special type of constructions at the discourse level, which have a fixed form and serve as a typical response in the dialogue. Unlike traditional constructions [4, 5, 6], they do not contain variables within the ...
Added: October 31, 2019
An Experimental Study of Hybrid Machine Learning Models for Extracting Named Entities
Lei J., Bolshakova E. I., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019. P. 50–60.
The paper describes two hybrid neural network models for named entity recognition (NER) in texts, namely Bi-LSTM-CRF and Gated-CNN-CRF, as well as results of experiments with them. ...
Added: November 3, 2019
Terminological Information Extraction from Russian Scientific Texts: Methods and Applications
Bolshakova E. I., Efremova N., Ivanov K., , in: Proceedings of Third Workshop "Computational linguistics and language science"Issue 4.: Manchester: EasyChair, 2019. P. 95–106.
Scientific texts contain a lot of special terms, which together with their definitions present an important part of scientific knowledge to be extracted for various applications, such as text summarization, construction of glossaries and ontologies and so on. The paper reports rule-based methods developed for extracting terminological information involving recognition of term definitions, as well ...
Added: November 3, 2019
Research target: Computer Science
Priority areas: humanitarian engineering science
Language: English
DOI
Text on another site
Keywords: information extractionconvolutional neural networksNeural Language Processing (NLP)corpus tools of linguistic analysis
Proceedings of Third Workshop "Computational linguistics and language science"
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