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Automated Metaphor Identification in Russian and Its Implications for Metaphor Studies
Ch. 8. P. 86–96.
Petrosian O., Ци Д., Zhang Y., IEEE Access 2025 Vol. 13 P. 208123–208137
This work presents a practical, explainability-guided pipeline for time-series forecasting that integrates automated lag engineering, XAI-based feature selection, and a lightweight, post-hoc calibration of a tree-ensemble forecaster. Rather than proposing a new forecasting paradigm, we show that FI-SHAP explanations stabilized by global feature-usage can flag redundant lag features for removal, and an exponential-smoothing–anchored calibration of ...
Added: September 21, 2026
Абрамов А. С., Chernyshev V. L., Mikhaylets E. et al., / Series Social Science Research Network "Social Science Research Network". 2025.
Computer vision is one of the most relevant modern research areas with broad practical applications. However, traditional solutions based on deep learning have signicant limitations and can be misleading. Topological data analysis, on the other hand, is a modern approach to solving similar problems using mathematically deterministic methods of algebraic topology that reduce the risk ...
Added: September 23, 2025
Aleksei Riabykh, Suleimanov I., Nagovitcyn I. et al., EPJ Data Science 2025 Vol. 14 Article 17
Changes in individual and institutional financial behavior leading to shifts in liquidity flows often depend on events reflected in news. However, the task of establishing relationship between financial behavior and news remains challenging and understudied. We propose a news-based feature generation approach that allows accounting for news events in liquidity flow time-series predicting tasks, thereby ...
Added: August 5, 2025
Ivan Vorobyev, Krivitskaya A., Computers and Security 2022 Vol. 120 Article 102786
Fraud detection in bank payments transactions suffers from a high number of false positives. To deal with this problem, we introduce a rules generation framework for a fraud-detection system – an automatic rules generation using distributed tree-based ML (machine learning) algorithms such as Decision Tree, Random Forest and Gradient Boosting, where the components of expert ...
Added: June 8, 2022
Chistova E., Shelmanov A., Kobozeva M. et al., , in: Computational Linguistics and Intellectual Technologies Papers from the Annual International Conference “Dialogue” (2019)Issue 18.: M.: Russian State University for the Humanitie, 2019. P. 163–176.
The paper considers the task of automatic discourse parsing of texts in Russian. Discourse parsing is a well-known approach to capturing text semantics across boundaries of single sentences. Discourse annotation was found to be useful for various tasks including summarization, sentiment analysis, question-answering. Recently, the release of manually annotated Ru-RSTreebank corpus unlocked the possibility of ...
Added: October 16, 2019
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