Ioannis Arapakis

2.3k total citations · 1 hit paper
39 papers, 1.3k citations indexed

About

Ioannis Arapakis is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ioannis Arapakis has authored 39 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Information Systems, 14 papers in Artificial Intelligence and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ioannis Arapakis's work include Recommender Systems and Techniques (12 papers), Topic Modeling (7 papers) and Mobile Crowdsensing and Crowdsourcing (6 papers). Ioannis Arapakis is often cited by papers focused on Recommender Systems and Techniques (12 papers), Topic Modeling (7 papers) and Mobile Crowdsensing and Crowdsourcing (6 papers). Ioannis Arapakis collaborates with scholars based in Spain, United Kingdom and United States. Ioannis Arapakis's co-authors include Joemon M. Jose, Alexandros Karatzoglou, Irene Lopatovska, Xiangnan He, Fajie Yuan, B. Barla Cambazoğlu, Xin Xin, Xiao Bai, Mounia Lalmas and Philip Gray and has published in prestigious journals such as IEEE Transactions on Knowledge and Data Engineering, Frontiers in Human Neuroscience and Information Processing & Management.

In The Last Decade

Ioannis Arapakis

37 papers receiving 1.2k citations

Hit Papers

A Simple Convolutional Generative Network for Next Item R... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ioannis Arapakis Spain 17 719 548 259 200 178 39 1.3k
Tuukka Ruotsalo Finland 22 686 1.0× 683 1.2× 338 1.3× 96 0.5× 100 0.6× 115 1.6k
Nava Tintarev United Kingdom 17 697 1.0× 688 1.3× 242 0.9× 172 0.9× 167 0.9× 49 1.3k
Marko Tkalčič Slovenia 20 499 0.7× 334 0.6× 450 1.7× 79 0.4× 245 1.4× 88 1.5k
Mark Rosenstein United States 10 583 0.8× 303 0.6× 192 0.7× 117 0.6× 116 0.7× 25 1.0k
Georg Buscher Germany 20 545 0.8× 267 0.5× 350 1.4× 42 0.2× 160 0.9× 38 1.4k
Mária Bieliková Slovakia 19 865 1.2× 790 1.4× 200 0.8× 61 0.3× 176 1.0× 186 1.6k
Siddharth Patwardhan United States 18 616 0.9× 2.7k 4.9× 243 0.9× 140 0.7× 119 0.7× 38 3.1k
Akrivi Katifori Greece 20 242 0.3× 468 0.9× 489 1.9× 38 0.2× 153 0.9× 91 1.3k
Federica Cena Italy 18 409 0.6× 266 0.5× 224 0.9× 44 0.2× 250 1.4× 102 1.3k
Bill Kules United States 15 412 0.6× 269 0.5× 215 0.8× 40 0.2× 66 0.4× 30 932

Countries citing papers authored by Ioannis Arapakis

Since Specialization
Citations

This map shows the geographic impact of Ioannis Arapakis'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 Ioannis Arapakis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ioannis Arapakis more than expected).

Fields of papers citing papers by Ioannis Arapakis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ioannis Arapakis. 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 Ioannis Arapakis. The network helps show where Ioannis Arapakis may publish in the future.

Co-authorship network of co-authors of Ioannis Arapakis

This figure shows the co-authorship network connecting the top 25 collaborators of Ioannis Arapakis. A scholar is included among the top collaborators of Ioannis Arapakis 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 Ioannis Arapakis. Ioannis Arapakis 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.
Arapakis, Ioannis, et al.. (2025). Corrigendum: Diffusion Models for Tabular Data Imputation and Synthetic Data Generation. ACM Transactions on Knowledge Discovery from Data. 19(8). 1–1. 1 indexed citations
2.
Wang, Jie, Alexandros Karatzoglou, Ioannis Arapakis, & Joemon M. Jose. (2025). Large Language Model driven Policy Exploration for Recommender Systems. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 107–116. 1 indexed citations
3.
Xin, Xin, et al.. (2025). Efficient and Effective Adaptation of Multimodal Foundation Models in Sequential Recommendation. IEEE Transactions on Knowledge and Data Engineering. 37(12). 7076–7089.
4.
Wang, Jie, Alexandros Karatzoglou, Ioannis Arapakis, & Joemon M. Jose. (2024). Reinforcement Learning-based Recommender Systems with Large Language Models for State Reward and Action Modeling. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 375–385. 9 indexed citations
5.
Xin, Xin, Alexandros Karatzoglou, Ioannis Arapakis, & Joemon M. Jose. (2022). Supervised Advantage Actor-Critic for Recommender Systems. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1186–1196. 17 indexed citations
6.
Leiva, Luis A. & Ioannis Arapakis. (2020). The Attentive Cursor Dataset. Frontiers in Human Neuroscience. 14. 565664–565664. 7 indexed citations
7.
Yuan, Fajie, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose, & Xiangnan He. (2019). A Simple Convolutional Generative Network for Next Item Recommendation. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 582–590. 353 indexed citations breakdown →
8.
Yuan, Fajie, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose, & Xiangnan He. (2018). A Simple but Hard-to-Beat Baseline for Session-based Recommendations.. arXiv (Cornell University). 4 indexed citations
9.
Vrochidis, Stefanos, Anastasia Moumtzidou, Ilias Gialampoukidis, et al.. (2018). A Multimodal Analytics Platform for Journalists Analyzing Large-Scale, Heterogeneous Multilingual, and Multimedia Content. Frontiers in Robotics and AI. 5. 123–123. 1 indexed citations
10.
Bai, Xiao, Ioannis Arapakis, B. Barla Cambazoğlu, & Ana Freire. (2017). Understanding and Leveraging the Impact of Response Latency on User Behaviour in Web Search. ACM Transactions on Information Systems. 36(2). 1–42. 18 indexed citations
11.
Arapakis, Ioannis & Luis A. Leiva. (2016). Predicting User Engagement with Direct Displays in Web Search Using Mouse Cursor Features. International ACM SIGIR Conference on Research and Development in Information Retrieval. 1 indexed citations
12.
Arapakis, Ioannis, et al.. (2016). Linguistic Benchmarks of Online News Article Quality. 1893–1902. 8 indexed citations
13.
Aiello, Luca Maria, Ioannis Arapakis, Ricardo Baeza‐Yates, et al.. (2016). The Role of Relevance in Sponsored Search. 185–194. 9 indexed citations
14.
Arapakis, Ioannis, Luis A. Leiva, & B. Barla Cambazoğlu. (2015). Know Your Onions. 1695–1698. 8 indexed citations
15.
Marcos, Mari‐Carmen, et al.. (2015). Effect of Snippets on User Experience in Web Search. 1–8. 14 indexed citations
16.
Arapakis, Ioannis, Mounia Lalmas, & George Valkanas. (2014). Understanding Within-Content Engagement through Pattern Analysis of Mouse Gestures. 1439–1448. 41 indexed citations
17.
Arapakis, Ioannis, Ioannis Konstas, & Joemon M. Jose. (2009). Using facial expressions and peripheral physiological signals as implicit indicators of topical relevance. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 461–470. 50 indexed citations
18.
Arapakis, Ioannis, et al.. (2009). Enriching user profiling with affective features for the improvement of a multimodal recommender system. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1–8. 36 indexed citations
19.
Arapakis, Ioannis, Joemon M. Jose, & Philip Gray. (2008). Affective feedback. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 395–402. 74 indexed citations
20.
Arapakis, Ioannis. (2008). Affective feedback. 891–891. 3 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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