Aleksandr Farseev

465 total citations
21 papers, 276 citations indexed

About

Aleksandr Farseev is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Aleksandr Farseev has authored 21 papers receiving a total of 276 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Information Systems, 11 papers in Artificial Intelligence and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Aleksandr Farseev's work include Recommender Systems and Techniques (9 papers), Complex Network Analysis Techniques (5 papers) and Digital Marketing and Social Media (4 papers). Aleksandr Farseev is often cited by papers focused on Recommender Systems and Techniques (9 papers), Complex Network Analysis Techniques (5 papers) and Digital Marketing and Social Media (4 papers). Aleksandr Farseev collaborates with scholars based in Singapore, Russia and Australia. Aleksandr Farseev's co-authors include Tat‐Seng Chua, Andrey Filchenkov, Liqiang Nie, Mohammad Akbari, Sergey Nikolenko, Meng Wang, Luming Zhang, Richang Hong, Jari Veijalainen and Denis Kotkov and has published in prestigious journals such as ACM Transactions on Information Systems, ACM Transactions on Intelligent Systems and Technology and Frontiers in Big Data.

In The Last Decade

Aleksandr Farseev

19 papers receiving 268 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Aleksandr Farseev Singapore 10 139 132 79 50 46 21 276
Gen Hattori Japan 9 83 0.6× 118 0.9× 123 1.6× 43 0.9× 30 0.7× 26 306
Ming Dong China 9 74 0.5× 155 1.2× 26 0.3× 73 1.5× 63 1.4× 18 268
Ignacio Fernández-Tobías Spain 9 288 2.1× 197 1.5× 88 1.1× 53 1.1× 15 0.3× 16 402
Hao Fu China 9 144 1.0× 164 1.2× 56 0.7× 47 0.9× 40 0.9× 11 278
Yanen Li United States 10 156 1.1× 148 1.1× 63 0.8× 21 0.4× 16 0.3× 15 286
Pei-Yun Hsueh United States 10 66 0.5× 275 2.1× 53 0.7× 32 0.6× 12 0.3× 36 453
Ante Odić Slovenia 7 175 1.3× 105 0.8× 82 1.0× 27 0.5× 11 0.2× 12 292
Naohiro Matsumura Japan 9 65 0.5× 117 0.9× 33 0.4× 60 1.2× 70 1.5× 48 247
Tanmay Basu India 8 64 0.5× 154 1.2× 24 0.3× 27 0.5× 17 0.4× 16 273
Michal Shmueli-Scheuer Israel 10 52 0.4× 158 1.2× 26 0.3× 22 0.4× 16 0.3× 32 247

Countries citing papers authored by Aleksandr Farseev

Since Specialization
Citations

This map shows the geographic impact of Aleksandr Farseev's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Aleksandr Farseev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aleksandr Farseev more than expected).

Fields of papers citing papers by Aleksandr Farseev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Aleksandr Farseev. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Aleksandr Farseev. The network helps show where Aleksandr Farseev may publish in the future.

Co-authorship network of co-authors of Aleksandr Farseev

This figure shows the co-authorship network connecting the top 25 collaborators of Aleksandr Farseev. A scholar is included among the top collaborators of Aleksandr Farseev based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Aleksandr Farseev. Aleksandr Farseev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Farseev, Aleksandr, et al.. (2025). Fusing Predictive and Large Language Models for Actionable Recommendations in Creative Marketing. ACM Transactions on Information Systems. 43(5). 1–31.
2.
Tzelepis, Christos, et al.. (2023). "Just To See You Smile": SMILEY, a Voice-Guided <strike>GUY</strike> GAN. 1196–1199. 2 indexed citations
3.
Nikolenko, Sergey, et al.. (2023). SoCraft: Advertiser-level Predictive Scoring for Creative Performance on Meta. 1132–1135. 2 indexed citations
4.
Nikolenko, Sergey, et al.. (2023). Against Opacity: Explainable AI and Large Language Models for Effective Digital Advertising. 9299–9305. 4 indexed citations
5.
6.
Farseev, Aleksandr, et al.. (2022). Do we behave differently on Twitter and Facebook: Multi-view social network user personality profiling for content recommendation. Frontiers in Big Data. 5. 931206–931206. 8 indexed citations
7.
Nikolenko, Sergey, et al.. (2022). Personality-Driven Social Multimedia Content Recommendation. Proceedings of the 30th ACM International Conference on Multimedia. 7290–7299. 12 indexed citations
8.
9.
Farseev, Aleksandr, et al.. (2020). I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence. 34(10). 13971–13972. 3 indexed citations
10.
Farseev, Aleksandr, et al.. (2019). A Whole New Ball Game: Harvesting Game Data for Player Profiling. Proceedings of the AAAI Conference on Artificial Intelligence. 33(1). 10025–10026. 2 indexed citations
11.
Farseev, Aleksandr, et al.. (2018). SoMin.ai. 1234–1236. 12 indexed citations
12.
Farseev, Aleksandr, et al.. (2017). Towards User Personality Profiling from Multiple Social Networks. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 26 indexed citations
13.
Farseev, Aleksandr & Tat‐Seng Chua. (2017). Tweet Can Be Fit. ACM Transactions on Information Systems. 35(4). 1–34. 15 indexed citations
14.
Nie, Liqiang, Luming Zhang, Meng Wang, et al.. (2017). Learning User Attributes via Mobile Social Multimedia Analytics. ACM Transactions on Intelligent Systems and Technology. 8(3). 1–19. 21 indexed citations
15.
Farseev, Aleksandr, et al.. (2017). Automatic classification of physical exercises from wearable sensors using small dataset from non-laboratory settings. Griffith Research Online (Griffith University, Queensland, Australia). 111–114. 3 indexed citations
16.
Farseev, Aleksandr, et al.. (2017). Cross-Domain Recommendation via Clustering on Multi-Layer Graphs. National University of Singapore. 195–204. 46 indexed citations
17.
Farseev, Aleksandr, et al.. (2016). bBridge. National University of Singapore. 759–761. 10 indexed citations
18.
19.
Farseev, Aleksandr, Liqiang Nie, Mohammad Akbari, & Tat‐Seng Chua. (2015). Harvesting Multiple Sources for User Profile Learning. 235–242. 62 indexed citations
20.
Farseev, Aleksandr, Denis Kotkov, Alexander Semenov, Jari Veijalainen, & Tat‐Seng Chua. (2015). Cross-Social Network Collaborative Recommendation. 1–2. 12 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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