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July 16, 2026
Team Success: Aligning Means with Objectives
In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.
July 15, 2026
Economists Propose More Effective Approach to Reducing Smoking
Economists at HSE University have examined how smokers respond to changes in cigarette prices. When tobacco prices increase, cigarette consumption does not always decline. In fact, spending on tobacco may even rise: according to the researchers, a 1% decrease in cigarette affordability leads to a 0.28% increase in per capita tobacco expenditure. The findings suggest that to reduce smoking rates, tobacco prices must rise faster than household incomes. The study has been published in Voprosy Statistiki.
July 15, 2026
HSE MIEM Students to Develop Two Satellites from Scratch for Orbital Experiments
The devices, created by student teams, will conduct space research on the properties of promising solar cells, on-board energy storage systems, and serial electronics for student satellites.

 

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Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, Proceedings

Issue 930. Switzerland : Springer, 2018.
Under the general editorship: D. Ustalov, A. Filchenkov, L. Pivovarova, J. Žižka

This book constitutes the refereed proceedings of the 7th Conference on Artificial Intelligence and Natural Language, AINL 2018, held in St. Petersburg, Russia, in October 2018. The 19 revised full papers were carefully reviewed and selected from 56 submissions and cover a wide range of topics, including morphology and word-level semantics, sentence and discourse representations, corpus linguistics, language resources, and social interaction analysis. 

Chapters
A Multi-Feature Classifier for Verbal Metaphor Identification in Russian Texts
Badryzlova Y., Panicheva P., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. Ch. 3 P. 23–34.
The paper presents a supervised machine learning experiment with multiple features for identification of sentences containing verbal metaphors in raw Russian text. We introduce the custom-created training dataset, describe the feature engineering techniques, and discuss the results. The following set of features is applied: distributional semantic features, lexical and morphosyntactic co-occurrence frequencies, flag words, quotation ...
Added: August 30, 2018
Employing Wikipedia data for coreference resolution in Russian
Azerkovich I., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. P. 107–112.
Semantic information has been deemed a valuable resource for solving the task of coreference resolution by many researchers. Unfortunately, not much has been done in the direction of using this data when working with Russian data. This work describes the first step of a research, attempting to create a coreference resolution system for Russian based on semantic data, concerned with ...
Added: September 5, 2018
Automatic Mining of Discourse Connectives for Russian
Toldova S., Pisarevskaya D., Kobozeva M., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. P. 79–87.
The identification of discourse connectives plays an important role in many discourse processing approaches. Among them there are functional words usually enumerated in grammars (iz-za ‘due to’, blagodarya ‘thanks to’,) and not grammaticalized expressions (X vedet k Y ‘X leads to Y’, prichina etogo ‘the cause is’). Both types of connectives signal certain relations between ...
Added: October 26, 2018
Stierlitz Meets SVM: Humor Detection in Russian
Ermilov A., Murashkina N., Goryacheva V. et al., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. P. 178–184.
In this paper, we investigate the problem of the humor detection for Russian language. For experiments, we used a large collection of jokes from social media and a contrast collection of non-funny sentences, as well as a small collection of puns. We implemented a large set of features and trained several SVM classifiers. The results ...
Added: November 9, 2018
Cleaning Up After a Party: Post-processing Thesaurus Crowdsourced Data
Antropova O., Arslanova E., Shaposhnikov M. et al., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. P. 133–138.
The study deals with post-processing of a noisy collection of synsets created using crowdsourcing. First, we cluster long synsets in three different ways. Second, we apply four cluster cleaning techniques based either on word popularity or word embeddings. Evaluation shows that the method based on word embeddings and existing dictionary definitions delivers best results. ...
Added: November 9, 2018
Lemmatization for ancient languages: Rules or neural networks?
Dereza O., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. P. 35–47.
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: November 14, 2018
Four Keys to Topic Interpretability in Topic Modeling
Mavrin A., Filchenkov A., Koltsov S., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. P. 117–129.
Added: November 30, 2018
Profiling the Age of Russian Bloggers
Litvinova T., Sboev A., Panicheva P., , in: Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, ProceedingsIssue 930.: Switzerland: Springer, 2018. P. 167–177.
The task of predicting demographics of social media users, bloggers and authors of other types of online texts is crucial for marketing, security, etc. However, most of the papers in authorship profiling deal with author gender prediction. In addition, most of the studies are performed in English-language corpora and very little work in the area ...
Added: February 19, 2019
Research target: Computer Science Philology and Linguistics
Priority areas: IT and mathematics
Language: English
DOI
Text on another site
Keywords: text miningmachine learningrobotics information retrievalartificial intelligencespeech technologiesdialogue systems
Artificial Intelligence and Natural Language, 7th International Conference, AINL 2018, St. Petersburg, Russia, October 17–19, 2018, Proceedings
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