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October 5, 2026
‘The Climate Transition Is Not Necessarily a Limitation for Business
Linara Khadimullina works in the field of low-carbon development. In an interview with the Young Scientists of HSE project, she spoke about why nature is not just a beautiful backdrop, her research on the role of sustainable corporate governance in reducing greenhouse gas emissions, and growing plants as a source of inspiration.
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Africa, Youth, and Civic Dialogue: Public Diplomacy Discussed at HSE University
In late September, HSE University hosted a roundtable discussion titled Civil Society in African Countries and Youth Participation in Public Diplomacy. Representatives of non-governmental organisations from Ghana, Ethiopia, and Russia, along with students from HSE University’s Bachelor’s Programme in Public Administration, discussed how young people without official diplomatic status can influence relations between countries and how the nonprofit sector can remain sustainable amid declining grant funding.
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HSE Researchers Show How Congenital Motor Disorders Affect Brain Development
Researchers from HSE University’s Institute for Cognitive Neuroscience have synthesised the findings of their previous studies on brain development in children with obstetric brachial plexus palsy and arthrogryposis. Their analysis shows that impaired motor function in early childhood not only limits children’s motor experience but also affects memory, categorical thinking, and information processing. The study has been published in Frontiers in Psychology.

 

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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.

Research target: Computer Science
Language: English
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Keywords: text analysisnatural language processingcollaborative filteringfeature extractionRecommender SystemsAspect-Based Sentiment Analysis
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