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Word Embedding for Semantically Related Words: An Experimental Study
Automatic Control and Computer Sciences. 2019. Vol. 53. P. 638–643.
The ability to identify semantic relations between words has made a word2vec model widely used in NLP tasks. The idea of word2vec is based on a simple rule that a higher similarity can be reached if two words have a similar context. Each word can be represented as a vector, so the closest coordinates of vectors can be interpreted as similar words. It allows to establish semantic relations (synonymy, relations of hypernymy and hyponymy and other semantic relations) by applying an automatic extraction. The extraction of semantic relations by hand is considered as a time-consuming and biased task, requiring a large amount of time and some help of experts. Unfortunately, the word2vec model provides an associative list of words which does not consist of relative words only. In this paper, we show some additional criteria that may be applicable to solve this problem. Observations and experiments with well-known characteristics, such as word frequency, a position in an associative list, might be useful for improving results for the extraction of semantic relations for the Russian language by using word embedding. In the experiments, the word2vec model trained on the Flibusta and pairs from Wiktionary are used as examples with semantic relationships. Semantically related words are applicable to thesauri, ontologies and intelligent systems for natural language processing.
Shipilov F., Barnyakov A., Ivanov A. et al., / Series Physics "arxiv.org". 2026.
A fast simulation of the detector response is a vital task in high-energy physics (HEP). Traditional Monte-Carlo methods form the backbone of modern particle physics simulation software but are computationally expensive. We present a machine-learning-based approach to fast simulation of the Focusing Aerogel Ring Imaging Cherenkov (FARICH) detector response. Given a particle track and momentum, ...
Added: May 19, 2026
Derkacheva A., Sakirkina M., Kraev G. et al., /. 2026.
Comprehensive data on natural hazards and their consequences are crucial for effective for risk assessment, adaptation planning, and emergency response. However, many countries face challenges with fragmented, inconsistent, and inaccessible data, particularly regarding local-scale events. To address this data gap in Russia, we developed an end-to-end processing pipeline that scrapes news from various online sources, ...
Added: April 28, 2026
Pilé I., Deng Y., Shchur L., / Series arXiv "math". 2026. No. 2604.10254.
We investigate the spatial overlap of successive spin configurations in Markov chain Monte Carlo simulations using the local Metropolis algorithm and the Svendsen-Wang and Wolff cluster algorithms. We examine the dynamics of these algorithms for two models in different universality classes: the Ising model and the Potts model with three components. The overlap of two ...
Added: April 20, 2026
Gabdullin N., Androsov I., / Series Computer Science "arxiv.org". 2026.
Label prediction in neural networks (NNs) has O(n) complexity proportional to the number of classes. This holds true for classification using fully connected layers and cosine similarity with some set of class prototypes. In this paper we show that if NN latent space (LS) geometry is known and possesses specific properties, label prediction complexity can ...
Added: April 2, 2026
Sorokin K., Beketov M., Онучин А. et al., / arxiv.org. Серия cs.SI "Social and Information Networks ". 2025.
Community detection in complex networks is a fundamental problem, open to new approaches in various scientific settings. We introduce a novel community detection method, based on Ricci flow on graphs. Our technique iteratively updates edge weights (their metric lengths) according to their (combinatorial) Foster version of Ricci curvature computed from effective resistance distance between the ...
Added: January 15, 2026
Petrovanov I., Sergeev A., / Series Computer Science "arxiv.org". 2025. No. 2512.18332.
Transport coding reduces message delay in packet-switched networks by introducing controlled redundancy at the transport layer: original packets are encoded into coded packets, and the message is reconstructed after the first successful deliveries, effectively shifting latency from the maximum packet delay to the -th order statistic. We present a concise, reproducible discrete-event implementation of transport coding in OMNeT++, including ...
Added: December 24, 2025
Hessian-based lightweight neural network for brain vessel segmentation on a minimal training dataset
Меньшиков И. А., Бернадотт А. К., Elvimov N. S., / Series arXie "Statistical mechanics". 2025.
Accurate segmentation of blood vessels in brain magnetic resonance angiography (MRA) is essential for successful surgical procedures, such as aneurysm repair or bypass surgery. Currently, annotation is primarily performed through manual segmentation or classical methods, such as the Frangi filter, which often lack sufficient accuracy. Neural networks have emerged as powerful tools for medical image ...
Added: December 1, 2025
Chernyshov D., Satanin A., Shchur L., / Series arXiv "math". 2025.
We investigate the boundary separating regular and chaotic dynamics in the generalized Chirikov map, an extension of the standard map with phase-shifted secondary kicks. Lyapunov maps were computed across the parameter space (K,K(α, τ)) and used to train a convolutional neural network (ResNet18) for binary classification of dynamical regimes. The model reproduces the known critical ...
Added: November 21, 2025
Rubchinskiy A., Chubarova D., / Series WP7 "Математические методы анализа решений в экономике, бизнесе и политике". 2025. No. WP7/2025/01.
The article examines one of the most famous examples of socio-economic systems, characterized by significant uncertainty – the S&P-500 stock market, where shares of 500 largest US companies are traded. No assumptions are made about the probabilistic characteristics of the stock market. A flexible algorithm for daily trading has been developed, based on both known fixed data ...
Added: November 9, 2025
Romanova T. V., В кн.: Когнитивные исследования языка. Вып. №1 (62): материалы Международной научной конференции по когнитивной лингвистике. 5-7 июня 2025. Ч.1Ч. 1. Кн. 62. Вып. 1.: Тюмень: ТюмГУ-Press, 2025. С. 447–450.
В статье рассмотрена классификация терминов когнитивной лингвистики по разным основаниям: по структуре, аутентичности, степени мотивированности, полисемантичности, а также по видам семантических отношений и оппозиций, в которые вступают термины в терминосистеме. ...
Added: June 9, 2025
Glavas G., Franco-Salvador M., Ponzetto S. et al., Knowledge-Based Systems 2018 Vol. 143 P. 1–9
Recognizing semantically similar sentences or paragraphs across languages is beneficial for many tasks, ranging from cross-lingual information retrieval and plagiarism detection to machine translation. Recently proposed methods for predicting cross-lingual semantic similarity of short texts, however, make use of tools and resources (e.g., machine translation systems, syntactic parsers or named entity recognition) that for many ...
Added: October 29, 2020
Gharavi E., Veisi H., Россо П., Neural Computing and Applications 2020 Vol. 32 No. 14 P. 10593–10607
The efficiency and scalability of plagiarism detection systems have become a major challenge due to the vast amount of available textual data in several languages over the Internet. Plagiarism occurs in different levels of obfuscation, ranging from the exact copy of original materials to text summarization. Consequently, designed algorithms to detect plagiarism should be robust ...
Added: October 29, 2020
Korogodina O., Karpik O., Klyshinsky E., , in: GraphiCon 2020 - Proceedings of the 30th International Conference on Computer Graphics and Machine Vision.: St. Petersburg: CEUR-WS, 2020.
Authors of Word2Vec claimed that their technology could solve the word analogy problem using the vector transformation in the introduced vector space. However, the practice demonstrates that it is not always true. In this paper, we investigate several Word2Vec and FastText model trained for the Russian language and find out reasons of such inconsistency. We ...
Added: October 21, 2020
Arefyev N V., Fedoseev M., Kabanov A. et al., , in: Компьютерная лингвистика и интеллектуальные технологии: по материалам ежегодной международной конференции «Диалог» (Москва, 17–20 июня 2020 г.)Issue 19(26): дополнительный том.: -, 2020. P. 13–32.
Expert-built lexical resources are known to provide information of good quality for the cost of low coverage. This property limits their applicability in modern NLP applications. Building descriptions of lexical-semantic relations manually in sufficient volume requires a huge amount of qualified human labour. However, given some initial version of a taxonomy is already built, automatic ...
Added: October 9, 2020
Arefyev, N., Ermolaev P., Panchenko A., , in: Computational Linguistics and Intellectual Technologies. International Conference "Dialogue 2018" Proceedings.: M.: Conference Proceedings Editorial board, 2018. P. 68–84.
The paper describes our participation in the first shared task on word sense induction and disambiguation for the Russian language RUSSE'2018 [Panchenko et al., 2018]. For each of several dozens of ambiguous words, the participants were asked to group text fragments containing it according to the senses of this word, which were not provided beforehand, ...
Added: October 9, 2020
Ekaterina Artemova, Bakarov A., Artemov A. et al., Journal of Cognitive Science 2020 Vol. 1 No. 21 P. 15–52
In this paper, our focus is the connection and influence of language technologies on the research in neurolinguistics. We present a review of brain imaging-based neurolinguistics studies with a focus on the natural language representations, such as word embeddings and pre-trained language model. Mutual enrichment of neurolinguistics and language technologies leads to development of brain-aware natural ...
Added: January 17, 2020
Zobnin A., Elistratova E., , in: Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)Issue W19-43.: Association for Computational Linguistics, 2019. P. 244–249.
Most word embedding algorithms such as word2vec or fastText construct two sort of vectors: for words and for contexts. Naive use of vectors of only one sort leads to poor results. We suggest using indefinite inner product in skip-gram negative sampling algorithm. This allows us to use only one sort of vectors without loss of ...
Added: November 9, 2019
Puzyrev D., Shelmanov A., Panchenko A. et al., , in: Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing, 2019, Florence, Italy, Association for Computational Linguistics.: Association for Computational Linguistics, 2019. P. 56–62.
aper presents the first gold-standard resource for Russian annotated with compositionality information of noun compounds. The compound phrases are collected from the Universal Dependency treebanks according to part of speech patterns, such as ADJ+NOUN or NOUN+NOUN, using the gold-standard annotations. Each compound phrase is annotated by two experts and a moderator according to the following ...
Added: October 30, 2019
Puzyrev D. A., Shelmanov A., Panchenko A. et al., , in: Analysis of Images, Social Networks and Texts. 8th International Conference AIST 2019.: Springer, 2019. P. 218–229.
In this paper, we present the first gold-standard corpus of Russian noun compounds annotated with compositionality information. We used Universal Dependency treebanks to collect noun compounds according to part of speech patterns, such as ADJ-NOUN or NOUN-NOUN and annotated them according to the following schema: a phrase can be either compositional, non-compositional, or ambiguous (i.e., ...
Added: October 30, 2019
Karyaeva M., Braslavski P., Kiselev Y., , in: Analysis of Images, Social Networks and Texts. 7th International Conference AIST 2018.: Springer, 2018. P. 76–87.
The paper investigates several techniques for hypernymy extraction from a large collection of dictionary definitions in Russian. First, definitions from different dictionaries are clustered, then single words and multiwords are extracted as hypernym candidates. A classification-based approach on pre-trained word embeddings is implemented as a complementary technique. In total, we extracted about 40K unique hypernym ...
Added: March 11, 2019
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
Voronkov Ilia, Amajd M., Kaimuldenov Z., , in: Actual Problems of System and Software Engineering 2017. Proceedings of the 5th International Conference on Actual Problems of System and Software Engineering Supported by Russian Foundation for Basic Research. Project #17-07-20565 Moscow, Russia, November 14-16, 2017, 408 P.Vol. 1989.: Aachen: CEUR Workshop Proceedings, 2017. P. 362–370.
In this paper, we analyze the use of different neural networks for the
text classification task. The accuracy of the studied text classifiers can be
changed by a small number of previously classified texts. This is important due
to the fact that in many applications of text classification a large number of unlabeled texts are easily accessible, while ...
Added: August 16, 2018
Zobnin A., , in: Analysis of Images, Social Networks and Texts. 6th International Conference, 2017, Revised Selected PapersVol. 10716.: Cham: Springer, 2018. Ch. 11 P. 116–128.
Consider a continuous word embedding model. Usually, the cosines between word vectors are used as a measure of similarity of words. These cosines do not change under orthogonal transformations of the embedding space. We demonstrate that, using some canonical orthogonal transformations from SVD, it is possible both to increase the meaning of some components and ...
Added: November 26, 2017
Wohlgenannt G., Artemova E., Ilvovsky D., , in: Proceedings of the Workshop on Language Technology Resources and Tools for Digital Humanities (LT4DH).: Osaka: [б.и.], 2016. Ch. 4 P. 18–26.
In this paper a social network is extracted from a literary text. The social network shows, how frequent the characters interact and how similar their social behavior is. Two types of similarity measures are used: the first applies co-occurrence statistics, while the second exploits cosine similarity on different types of word embedding vectors. The results ...
Added: March 6, 2017