Milan Marković

723 total citations
49 papers, 416 citations indexed

About

Milan Marković is a scholar working on Computer Science Applications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Milan Marković has authored 49 papers receiving a total of 416 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Computer Science Applications, 10 papers in Artificial Intelligence and 9 papers in Information Systems. Recurrent topics in Milan Marković's work include Mobile Crowdsensing and Crowdsourcing (11 papers), Genetic and phenotypic traits in livestock (8 papers) and Data Quality and Management (8 papers). Milan Marković is often cited by papers focused on Mobile Crowdsensing and Crowdsourcing (11 papers), Genetic and phenotypic traits in livestock (8 papers) and Data Quality and Management (8 papers). Milan Marković collaborates with scholars based in United Kingdom, Montenegro and United States. Milan Marković's co-authors include Peter Edwards, Georgios Leontidis, Jessica Enright, David R. Matthews, Caitlin Cottrill, Naomi Jacobs, Božidarka Marković, David Corsar, John D. Nelson and Wei Pang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Milan Marković

47 papers receiving 396 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Milan Marković United Kingdom 11 95 78 55 55 46 49 416
Daniel Jiménez Colombia 10 90 0.9× 43 0.6× 28 0.5× 135 2.5× 5 0.1× 25 567
Taufik Djatna Indonesia 14 101 1.1× 151 1.9× 109 2.0× 41 0.7× 8 0.2× 150 697
Petr Skobelev Russia 16 93 1.0× 90 1.2× 12 0.2× 56 1.0× 36 0.8× 85 859
Manlio Bacco Italy 16 32 0.3× 62 0.8× 72 1.3× 245 4.5× 18 0.4× 47 1.2k
Leanne Wiseman Australia 9 57 0.6× 71 0.9× 60 1.1× 171 3.1× 3 0.1× 32 498
Tim Verwaart Netherlands 11 24 0.3× 40 0.5× 62 1.1× 61 1.1× 13 0.3× 20 448
Annisa Annisa Indonesia 8 51 0.5× 69 0.9× 9 0.2× 47 0.9× 13 0.3× 110 284
J.L. Top Netherlands 13 396 4.2× 176 2.3× 78 1.4× 59 1.1× 4 0.1× 65 837
Pedro Luiz Pizzigatti Corrêa Brazil 13 74 0.8× 97 1.2× 36 0.7× 90 1.6× 6 0.1× 57 524
Akshit Singh United Kingdom 10 61 0.6× 108 1.4× 214 3.9× 68 1.2× 7 0.2× 17 1.2k

Countries citing papers authored by Milan Marković

Since Specialization
Citations

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

Fields of papers citing papers by Milan Marković

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Milan Marković

This figure shows the co-authorship network connecting the top 25 collaborators of Milan Marković. A scholar is included among the top collaborators of Milan Marković 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 Milan Marković. Milan Marković 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.
Marković, Milan, et al.. (2025). Semi-automated data provenance tracking for transparent data production and linkage to enhance auditing and quality assurance in Trusted Research Environments. International Journal for Population Data Science. 10(2). 2464–2464.
2.
Marković, Milan, Tewodros Alemu Ayall, Nicholas J. Watson, et al.. (2024). Embedding AI-Enabled Data Infrastructures for Sustainability in Agri-Food: Soft-Fruit and Brewery Use Case Perspectives. Sensors. 24(22). 7327–7327. 3 indexed citations
3.
Marković, Milan, et al.. (2023). Model pruning enables localized and efficient federated learning for yield forecasting and data sharing. Expert Systems with Applications. 242. 122847–122847. 16 indexed citations
4.
Jacobs, Naomi, et al.. (2022). Prototyping an IoT transparency toolkit to support communication, governance and policy in the smart city. The Design Journal. 25(3). 459–480. 3 indexed citations
5.
Marković, Milan, et al.. (2021). How might technology rise to the challenge of data sharing in agri-food?. Global Food Security. 28. 100493–100493. 53 indexed citations
6.
Pang, Wei, et al.. (2021). Towards Accountability Driven Development for Machine Learning Systems. 2894. 25–32. 1 indexed citations
7.
Marković, Božidarka, et al.. (2020). ASSOCIATION OF GENETIC VARIANTS OF β-LACTOGLOBULIN GENE WITH MILK TRAITS OF JEZEROPIVSKA SHEEP BREED. The Journal Agriculture and Forestry. 66(3). 2 indexed citations
8.
Marković, Božidarka, et al.. (2019). Differentiation of some Pramenka sheep breeds based on morphometric characteristics. Archives animal breeding/Archiv für Tierzucht. 62(2). 393–402. 22 indexed citations
9.
Marković, Milan, et al.. (2019). Factors Affecting Milk Yield and Composition of Indigenous Balkan Goat Breed Reared in Semi Extensive Conditions. Indian Journal of Animal Research. 6 indexed citations
10.
Asif, Waqar, et al.. (2019). User Privacy Risk Analysis For The Internet of Things. 259–264. 2 indexed citations
11.
Marković, Milan & Peter Edwards. (2019). Enhancing Transparency of MQTT Brokers For IoT Applications Through Provenance Streams. Aberdeen University Research Archive (Aberdeen University). 17–20. 4 indexed citations
12.
Schreier, Daniel, Milan Marković, & Saša Petković. (2018). "i sall synge in haboundance of gastly softne" : /h/ insertion in Middle English: methodology, data mining and some first interpretations. International Journal of English Studies. 23(23). 115–136. 2 indexed citations
13.
Marković, Milan & Peter Edwards. (2016). Semantic Stream Processing for IoT Devices in the Food Safety Domain. 1–4. 3 indexed citations
14.
Antunović, Zvonko, Božidarka Marković, Josip Novoselec, et al.. (2015). Blood MetaBolic profile and oxidative status of endangered Mediterranean sheep Breeds during pregnancy. Bulgarian Journal of Agricultural Science. 21(3). 655–661. 3 indexed citations
15.
Corsar, David, Milan Marković, Peter Edwards, et al.. (2015). TravelBot: Journey Disruption Alerts Utilising Social Media and Linked Data. Aberdeen University Research Archive (Aberdeen University). 1 indexed citations
16.
Antunović, Zvonko, et al.. (2014). Hematološki pokazatelji ugroženih pasmina ovaca - dubrovačke rude i zetske žuje. 537. 1 indexed citations
17.
Marković, Milan, Peter Edwards, & David Corsar. (2013). A role for provenance in social computation. International Semantic Web Conference. 93–95. 2 indexed citations
18.
Corsar, David, et al.. (2013). GetThere: a rural passenger information system utilising linked data & citizen sensing. International Semantic Web Conference. 85–88. 8 indexed citations
19.
Marković, Milan, Peter Edwards, David Corsar, & Jeff Z. Pan. (2012). The Crowd and the Web of Linked Data: A Provenance Perspective. National Conference on Artificial Intelligence. 50–51.
20.
Marković, Milan, et al.. (2012). Multicriteria decision-making in railway route planning and design. Journal of the Croatian Association of Civil Engineers. 64(3). 195–205. 27 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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