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SmartTips: Online Products Recommendations System Based on Analyzing Customers Reviews
Applied Sciences (Switzerland). 2022. Vol. 12. No. 17. Article 8823.
Ali N., Alshahrani A., Alghamdi A., Novikov B.
Online customers’ opinions represent a significant resource for both customers and enterprises to extract much information that helps them make the right decision. Finding relevant data while searching the internet is a big challenge for web users, known as the “Problem of Information Overload”. Recommender systems have been recognized as a promising way of solving such problems. In this paper, a product recommendation system called “SmartTips” is introduced. The proposed model is built based on aspect-based sentiment analysis, which exploits customers’ feedback and applies the aspect term extraction model to rate various products and extract user preferences as well. Several factors were considered, including readers’ votes, aspect term frequency, opinion words’ frequencies, etc. We tested our model on benchmark datasets that are widely used, and the results show that it outperforms the baseline methods regarding the mean squared errors of generated predictions.
Seul: PMLR, 2026.
Added: June 4, 2026
Silakov D., Системный администратор 2026 № 3 С. 28–33
В статье про платформы для разработки открытого ПО в Китае мы рассказали про GitCode – молодой проект, позиционируемый как площадка для разработчиков со всего мира. Сейчас на GitCode размещаются проекты, созданные в КНР, но некоторые из них уже известны и на международной арене. Помочь открытым проектам в становлении, развитии и расширению аудитории призван фонд OpenAtom ...
Added: June 2, 2026
Tyuryakova-Matveeva D., Цифровые гуманитарные исследования 2026 № 1 С. 4–26
The article explores cultural references in the works of Andrei Voznesensky by analyzing the personalities he mentions. A total of 1,678 works were processed, including poetry, prose, and early unpublished poems. NER methods based on Natasha, spaCy, and LLM Grok tools made it possible to study the frequency of mentions of famous people and their ...
Added: May 31, 2026
Slivnitsin P., Mylnikov L., Engineering Applications of Artificial Intelligence 2026 Vol. 179 Article 115185
The paper describes a applied artificial intelligence task of recognition-by-components method of real objects based on the recognition of a limited set of primitives or components. The recognition-by-components makes it possible to determine the components, that compose an object, and increase the number of recognizable objects without degrading the recognition quality. Training is performed on ...
Added: May 29, 2026
Mokienko O., Zisman M. A., Bobrov P. et al., American Journal of Physical Medicine and Rehabilitation 2026 Vol. 105 No. 6 P. 555–563
Brain-computer interfaces (BCIs) represent a promising technology for restoring lower limb motor functions and gait after stroke. The application of BCIs in this field is supported by a limited number of studies. The objective of the review was to systematically and critically evaluate the current evidence on the use of BCIs for lower limb function ...
Added: May 28, 2026
М.: Институт проблем управления им. В.А. Трапезникова РАН, 2024.
В сборник вошли материалы VIII Международной научной конференции «Информационные технологии и технические средства управления» (ICCT-2024). На конференции были рассмотрены вопросы, касающиеся перспектив развития научного приборостроения в телекоммуникационных и управляющих системах, биомедицинской информатики, аппаратного и программного обеспечения информационнокоммуникационных систем, надежности, диагностики и неразрушающего контроля, систем управления и автоматизации, цифровых экосистем, управления производством и логистикой, методов математического ...
Added: May 27, 2026
Degtyarev A., Bakhurin S., Yudin N., DSPA 2026 P. 1–6
This paper investigates one possible solution to the problem of self-interference cancellation (SIC) arising in the design of in-band full-duplex (IBFD) communication systems. Self-interference cancellation is performed in the digital domain using multilayer nonlinear models adapted via gradient-based optimization. The presence of local minima and saddle points during the adaptation of multilayer models limits the ...
Added: May 26, 2026
Androsov I., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 3 P. 87–114
This paper examines echo state networks (ESNs), one of the most prevalent approaches to
implementing reservoir computing. An ESN consists of a recurrent neural network with fixed (untrained)
weights and a readout layer that is typically linear and trainable. This approach enables the creation of energyefficient and computationally efficient neural networks capable of real-time learning. However, since ...
Added: May 26, 2026
Караваева Е. А., Кулигин Л. А., Rezunik L. et al., Труды Института системного программирования РАН 2026 Т. 38 № 3 С. 67–94
В статье представлен метод рефакторинга исходного кода на основе интеграции большой языковой модели (LLM) и расширенной UML-модели программного кода. Предложенный подход позволяет выявлять проблемные участки кода с использованием функций тревожности и структурных метрик классов, а затем выполнять автоматизированный рефакторинг. Ключевой особенностью метода является использование LLM для генерации формальных спецификаций на языке OCL (Object Constraint Language), ...
Added: May 24, 2026
Tyukin I., Tyukina T., van Helden D. P. et al., Information Sciences 2024 Vol. 678 Article 120856
AI errors pose a significant challenge, hindering real-world applications. This work introduces a novel approach to cope with AI errors using weakly supervised error correctors that guarantee a specific level of error reduction. Our correctors have low computational cost and can be used to decide whether to abstain from making an unsafe classification. We provide ...
Added: May 23, 2026
Zaikin A., Sviridov I., Sosedka A. et al., Technologies 2026 Vol. 14 No. 2 Article 84
High-dimensional tabular data are common in biomedical and clinical research, yet conventional machine learning methods often struggle in such settings due to data scarcity, feature redundancy, and limited generalization. In this study, we systematically evaluate Synolitic Graph Neural Networks (SGNNs), a framework that transforms high-dimensional samples into sample-specific graphs by training ensembles of low-dimensional pairwise ...
Added: May 23, 2026
Chertopolokhov V., Mukhamedov A., Bugriy G. et al., IEEE Access 2026 Vol. 14 P. 14369–14392
This study presents on-the-fly identification and multi-step prediction of nonlinear systems with delayed inputs using a dynamic neural network combined with a smooth projection onto ellipsoids. The projection enforces parameter constraints that guarantee stability, while a Lyapunov–Krasovskii analysis yields computable ultimate error bounds. Riccati-type matrix inequalities are derived, providing an efficient vectorization–projection–devectorization implementation suitable for ...
Added: May 22, 2026
Loshkareva M. E., Matveeva N., Вестник Томского государственного университета. История 2026 № 100 С. 112–118
This research is an endeavor to apply social network analysis (SNA) to the study of a medieval narrative source. The authors suppose that the use of network analysis may offer new possibilities in the study of the history of regions characterized by some political fragmentation. Authors tried to construct networks of historical interactions from 1193 ...
Added: May 22, 2026
Jin S., Komarov M. M., Scientific Reports 2026
Intrabody communication (IBC) channels offer physiological diversity that can be leveraged for passive biometric identification in wearable devices. Recent reports of over 99 per cent identification accuracy have frequently resulted from data leakage, where samples from the same subject are seen in both training and evaluation, yielding inflated and unreliable metrics. In this work, we ...
Added: May 21, 2026
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
Rabat: Association for Computational Linguistics, 2026.
Added: May 19, 2026
Malikov D., Krasnov L., Kiseleva M. et al., Scientific data 2026 Vol. 13 Article 727
Solubility is a crucial property of organic compounds, impacting their potential applications in synthetic chemistry, materials science and drug design. Moreover, in technological processes mixtures of solvents are often utilized, making the solubility assessment more complicated. Predicting solubility values in mixtures of solvents from a molecular structure can help to address this issue, although a ...
Added: May 19, 2026
Ankudinov I., Социология: методология, методы, математическое моделирование 2025 № 61 С. 165–203
The changing political mood of Russians is a constant subject of interest for sociological agencies. With the development of the Internet, conventional questionnaire research began to be supplemented by online surveys and, despite some skepticism, by social media mining. This article attempts to adjust an accidental web-sample so as to bring its estimates closer to ...
Added: April 22, 2026
Чудинова О. С., Первицкая Л. А., Ramenskaya A., Индустриальная экономика 2026 № 1 С. 65–78
This article is devoted to the development of an algorithm for analyzing news information using machine learning methods implemented in Python libraries. The choice of tools used at each stage of the algorithm is justified by calculating metrics for the quality of the solution to the corresponding machine learning problems. The algorithm’s results are presented ...
Added: April 20, 2026
Yusupov V., Sukhorukov N., Frolov E., User Modelling and User-Adapted Interaction 2026 Vol. 36 Article 2
Graph-based recommender systems have emerged as a powerful paradigm for personalized recommendations. However, their reliance on full model retraining to incorporate new users or new interactions creates scalability barriers. The task becomes infeasible in real-life recommender systems due to excessive time and resource costs involved. To address this limitation, we propose a fast and efficient ...
Added: March 15, 2026
Yusupov V., Sukhorukov N., Frolov E., User Modeling and User-Adapted Interaction 2025 P. 1–24
Graph-based recommender systems have emerged as a powerful paradigm for personalized recommendations. However, their reliance on full model retraining to incorporate new users or new interactions creates scalability barriers. The task becomes infeasible in real-life recommender systems due to excessive time and resource costs involved. To address this limitation, we propose a fast and efficient ...
Added: March 14, 2026
Biryukova K., Chelnokova D., Erkenova J. et al., Communications in Computer and Information Science 2024 Vol. 2364 CCIS P. 109 – 121
Added: February 25, 2026
Yusupov V., Sukhorukov N., Frolov E., , in: User Modeling and User-Adapted Interaction.: Springer, 2026. Ch. 36.2 P. 1–24.
Graph-based recommender systems have emerged as a powerful paradigm for personalized recommendations. However, their reliance on full model retraining to incorporate new users or new interactions creates scalability barriers. The task becomes infeasible in real-life recommender systems due to excessive time and resource costs involved. To address this limitation, we propose a fast and efficient ...
Added: January 29, 2026