Nikola Milošević

601 citations
14 papers · 280 indexed · 1 hit paper · h-index 5

Nikola Milošević

12 papers receiving 264 citations

Hit Papers

Machine learning aided Android malware classification215201720262020202350100150200

Peers

Nikola Milošević
Comparison fields: 5 of 55
  • Signal Processing 187
  • Software 64
  • Computer Networks and Communications 178
  • Information Systems 107
  • Artificial Intelligence 73
Replace Henrik Plate with:
Henrik Plate Italy
Moses Ashawa United Kingdom
Anton V. Uzunov Australia
Foyzul Hassan United States
Patrick Jauernig Germany
Taher A. Ghaleb Canada
James F. Terwilliger United States
Khurram Mustafa India
Yuval Fledel Israel
Gérard Wagener Luxembourg
Nikola Milošević relative to Henrik Plate Italy Henrik Plate's profile →
Citations per field
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Henrik Plate · 1×
Citations per year

Countries citing papers authored by Nikola Milošević

Since Specialization
Citations

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

Fields of papers citing papers by Nikola Milošević

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 12 scholars most cited alongside Nikola Milošević, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nikola Milošević Line = papers co-authored together Nikola Milošević links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20244
2 202416
3 20240
4 202223
5 20225
6 20202
7
Extraction of Drug-drug Interactions from Drug Product Labeling Tables
20171
8
Machine learning aided Android malware classificationbreakdown →
2017215
9 20162
10 20165
11
Android Security: Malicious use of Android permissions
20141
12
Table mining and data curation from biomedical literature
20142
13
History of malware
20130
14 20084

About Nikola Milošević

Nikola Milošević is a scholar working on Signal Processing, Software and Artificial Intelligence, having authored 14 papers that have together received 280 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (6 papers), Semantic Web and Ontologies (5 papers), Topic Modeling (5 papers), Advanced Malware Detection Techniques (3 papers), Advanced Text Analysis Techniques (2 papers), Knowledge Management and Sharing (1 paper), CCD and CMOS Imaging Sensors (1 paper) and Advanced Manufacturing and Logistics Optimization (1 paper). The work is most often cited by research in Signal Processing (187 citations), Software (64 citations) and Computer Networks and Communications (178 citations). Nikola Milošević has collaborated with scholars based in United Kingdom, Germany and Serbia. Frequent co-authors include Kim‐Kwang Raymond Choo, Ali Dehghantanha, Goran Nenadić, Aleksandar Kovačević, Ahmed Nabil Belbachir, Michael Hofstätter, Peter Schön, Abdullah Gök, Jovica V. Milanović and Jodi Schneider. Their work appears in journals such as Artificial Intelligence in Medicine, Scientific Data, Computers & Electrical Engineering, Journal of Web Semantics and Research Explorer (The University of Manchester).

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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