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July 9, 2026
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Researchers from the HSE Faculty of Economic Sciences have shown that the accuracy of birth rate forecasts for Russia can be improved by almost 50% by incorporating the dynamics of online search queries related to pregnancy and childbirth into forecasting models. In the best-performing models, the forecasting error fell from 4.6% to 3.2%. The findings have been published in Populations and Economics.
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?

Baselines and Symbol N-Grams: Simple Part-Of-Speech Tagging of Russian?

P. 9–19.
Arefyev, N.V., Ermolaev P.

We propose using NB-SVM over bag of character n-grams input representation for determining part-of-speech tags and grammatical categories like gender, number, etc. for words in Russian texts. Several methods are compared including CRF (Conditional Random Fields), SVM (Support Vector Machines) and NB-SVM (Naive Bayes SVM) and superiority of NB-SVM over other classifiers is shown. The proposed model is the 5th best among 12 other models in the first shared task of the MorphoRuEval-17 challenge. We also experimented with category grouping when a single classifier is used to determine several grammatical categories and showed that it improves the model per- formance even further.

Language: English
Text on another site
Keywords: POS-taggingmultilabel classificationSupport Vector Machines (SVM)

In book

Supplementary Proceedings of the Sixth International Conference on Analysis of Images, Social Networks and Texts (AIST-SUP 2017), Moscow, Russia, July 27-29, 2017
Vol. 1975. , Aachen: CEUR-WS.org, 2017.
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