Dimitris Spiliotopoulos

1.2k total citations
63 papers, 538 citations indexed

About

Dimitris Spiliotopoulos is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Dimitris Spiliotopoulos has authored 63 papers receiving a total of 538 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 26 papers in Information Systems and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in Dimitris Spiliotopoulos's work include Recommender Systems and Techniques (19 papers), Image and Video Quality Assessment (11 papers) and Speech and dialogue systems (8 papers). Dimitris Spiliotopoulos is often cited by papers focused on Recommender Systems and Techniques (19 papers), Image and Video Quality Assessment (11 papers) and Speech and dialogue systems (8 papers). Dimitris Spiliotopoulos collaborates with scholars based in Greece, Germany and United Kingdom. Dimitris Spiliotopoulos's co-authors include Costas Vassilakis, Dionisis Margaris, Konstantinos Kotis, George A. Vouros, Ion Androutsopoulos, Constantine D. Spyropoulos, Γεώργιος Κουρουπέτρογλου, Paraskevi Fragopoulou, Despoina Antonakaki and Sotiris Ioannidis and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

In The Last Decade

Dimitris Spiliotopoulos

58 papers receiving 514 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dimitris Spiliotopoulos Greece 13 227 183 107 96 51 63 538
Morgan Harvey United Kingdom 16 215 0.9× 400 2.2× 134 1.3× 108 1.1× 95 1.9× 54 803
Karën Fort France 8 263 1.2× 100 0.5× 74 0.7× 75 0.8× 26 0.5× 31 605
Boris Smus United States 8 210 0.9× 137 0.7× 93 0.9× 93 1.0× 89 1.7× 10 807
Júlio Cesar dos Reis Brazil 12 208 0.9× 96 0.5× 54 0.5× 45 0.5× 73 1.4× 77 431
Dmitri Roussinov United States 13 367 1.6× 248 1.4× 100 0.9× 48 0.5× 26 0.5× 48 623
Joon Sung Park United States 4 326 1.4× 61 0.3× 65 0.6× 80 0.8× 38 0.7× 6 642
Fabiana Vernero Italy 10 80 0.4× 134 0.7× 56 0.5× 64 0.7× 38 0.7× 40 302
Melanie Kellar Canada 15 87 0.4× 330 1.8× 85 0.8× 89 0.9× 170 3.3× 23 642
Ilaria Torre Italy 13 187 0.8× 273 1.5× 123 1.1× 143 1.5× 45 0.9× 58 511
Angelika Maag Australia 7 476 2.1× 213 1.2× 57 0.5× 96 1.0× 13 0.3× 22 795

Countries citing papers authored by Dimitris Spiliotopoulos

Since Specialization
Citations

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

Fields of papers citing papers by Dimitris Spiliotopoulos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dimitris Spiliotopoulos

This figure shows the co-authorship network connecting the top 25 collaborators of Dimitris Spiliotopoulos. A scholar is included among the top collaborators of Dimitris Spiliotopoulos 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 Dimitris Spiliotopoulos. Dimitris Spiliotopoulos 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.
Margaris, Dionisis, et al.. (2025). Using Prediction Confidence Factors to Enhance Collaborative Filtering Recommendation Quality. Technologies. 13(5). 181–181.
2.
3.
Margaris, Dionisis, et al.. (2025). An evaluation review of user similarity metrics in sparse collaborative filtering datasets. International Journal of Data Science and Analytics. 20(7). 6665–6693.
4.
Vassilakis, Costas, et al.. (2025). AI and Related Technologies in the Fields of Smart Agriculture: A Review. Information. 16(2). 100–100. 14 indexed citations
5.
Vassilakis, Costas, et al.. (2024). Artificial Intelligence Tools for the Agriculture Value Chain: Status and Prospects. Electronics. 13(22). 4362–4362. 22 indexed citations
6.
Margaris, Dionisis, et al.. (2024). Exploiting Rating Prediction Certainty for Recommendation Formulation in Collaborative Filtering. Big Data and Cognitive Computing. 8(6). 53–53. 2 indexed citations
7.
Vassilakis, Costas, et al.. (2024). The Implementation of “Smart” Technologies in the Agricultural Sector: A Review. Information. 15(8). 466–466. 11 indexed citations
8.
Margaris, Dionisis, Costas Vassilakis, Dimitris Spiliotopoulos, & Stefanos Ougiaroglou. (2023). Rating Prediction Quality Enhancement in Low-Density Collaborative Filtering Datasets. Big Data and Cognitive Computing. 7(2). 59–59. 2 indexed citations
9.
Margaris, Dionisis, et al.. (2023). Disruptive Technologies for Parliaments: A Literature Review. Future Internet. 15(2). 66–66. 6 indexed citations
10.
Spiliotopoulos, Dimitris, Dionisis Margaris, Costas Vassilakis, et al.. (2023). Chatbots for Cultural Venues: A Topic-Based Approach. Algorithms. 16(7). 339–339. 5 indexed citations
11.
Spiliotopoulos, Dimitris, Dionisis Margaris, & Costas Vassilakis. (2022). On Exploiting Rating Prediction Accuracy Features in Dense Collaborative Filtering Datasets. Information. 13(9). 428–428. 6 indexed citations
12.
Margaris, Dionisis, Costas Vassilakis, & Dimitris Spiliotopoulos. (2022). On Producing Accurate Rating Predictions in Sparse Collaborative Filtering Datasets. Information. 13(6). 302–302. 8 indexed citations
13.
Margaris, Dionisis, Dimitris Spiliotopoulos, & Costas Vassilakis. (2021). Augmenting Black Sheep Neighbour Importance for Enhancing Rating Prediction Accuracy in Collaborative Filtering. Applied Sciences. 11(18). 8369–8369. 3 indexed citations
14.
Margaris, Dionisis, Costas Vassilakis, & Dimitris Spiliotopoulos. (2020). What makes a review a reliable rating in recommender systems?. Information Processing & Management. 57(6). 102304–102304. 35 indexed citations
15.
Spiliotopoulos, Dimitris, et al.. (2020). Multimodal Interaction: Correlates of Learners’ Metacognitive Skill Training Negotiation Experience. Information. 11(8). 381–381. 3 indexed citations
16.
Margaris, Dionisis, et al.. (2020). An Algorithm for Density Enrichment of Sparse Collaborative Filtering Datasets Using Robust Predictions as Derived Ratings. Algorithms. 13(7). 174–174. 8 indexed citations
17.
Spiliotopoulos, Dimitris, Dionisis Margaris, & Costas Vassilakis. (2020). Data-Assisted Persona Construction Using Social Media Data. Big Data and Cognitive Computing. 4(3). 21–21. 27 indexed citations
18.
Vassilakis, Costas, Konstantinos Kotis, Dimitris Spiliotopoulos, et al.. (2020). A Semantic Mixed Reality Framework for Shared Cultural Experiences Ecosystems. Big Data and Cognitive Computing. 4(2). 6–6. 5 indexed citations
19.
Spiliotopoulos, Dimitris, et al.. (2020). Human behaviour in multimodal interaction: main effects of civic action and interpersonal and problem-solving skills. Journal of Ambient Intelligence and Humanized Computing. 11(12). 5991–6006. 9 indexed citations
20.
Antonakaki, Despoina, et al.. (2016). Investigating the complete corpus of referendum and elections tweets. 100–105. 11 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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