Pero Subašić
Impact in
- Artificial Intelligence top 5%
- Sentiment Analysis and Opinion Mining
- Advanced Text Analysis Techniques
- Topic Modeling
- Text and Document Classification Technologies
- Fuzzy Logic and Control Systems
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- Multi-Criteria Decision Making
Papers in
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- AI-based Problem Solving and Planning 4
- Fuzzy Logic and Control Systems 3
- Sentiment Analysis and Opinion Mining 2
- Advanced Text Analysis Techniques 2
- Topic Modeling 2
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- Web Data Mining and Analysis 2
- Co-authors
- Alison K. Huettner (2 shared papers)Kaoru Hirota (1 shared paper)Sanja Vraneš (3 shared papers)Benjamin Rey (1 shared paper)Rosie Jones (1 shared paper)Sayandev Mukherjee (1 shared paper)Lin Xiao (1 shared paper)
- Journals
- Engineering Applications of Artificial Intelligence (1 paper)European Journal of Operational Research (1 paper)Fuzzy Sets and Systems (1 paper)Expert Systems with Applications (1 paper)IEEE Transactions on Fuzzy Systems (1 paper)
- Partner nations
- SerbiaJapanUnited States
In The Last Decade
Pero Subašić
11 papers receiving 234 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 211
- Management Science and Operations Research 27
- Experimental and Cognitive Psychology 25
- Information Systems 42
- General Social Sciences 5
Countries citing papers authored by Pero Subašić
This map shows the geographic impact of Pero Subašić'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 Pero Subašić with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pero Subašić more than expected).
Fields of papers citing papers by Pero Subašić
This network shows the impact of papers produced by Pero Subašić. 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 Pero Subašić. The network helps show where Pero Subašić may publish in the future.
Co-authors
The 7 scholars most cited alongside Pero Subašić, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 193 | |
| 2 | 1998 | 20 | |
| 3 | 2002 | 14 | |
| 4 | 1994 | 10 | |
| 5 | 2007 | 6 | |
| 6 | 1992 | 5 | |
| 7 | 2002 | 4 | |
| 8 | Building Knowledge Base through Deep Learning Relation Extraction and Wikidata. | 2019 | 3 |
| 9 | 2014 | 3 | |
| 10 | 1994 | 3 | |
| 11 | Fazi logika i neuronske mreze | 1997 | 1 |
| 12 | 2002 | 0 |
About Pero Subašić
Pero Subašić is a scholar working on Artificial Intelligence, Information Systems, Computational Theory and Mathematics, Management Science and Operations Research and Control and Systems Engineering, having authored 12 papers that have together received 262 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (4 papers), Fuzzy Logic and Control Systems (3 papers), Sentiment Analysis and Opinion Mining (2 papers), Web Data Mining and Analysis (2 papers), Multi-Criteria Decision Making (2 papers), Advanced Text Analysis Techniques (2 papers), Topic Modeling (2 papers) and Rough Sets and Fuzzy Logic (2 papers). The work is most often cited by research in Artificial Intelligence (211 citations), Management Science and Operations Research (27 citations), Experimental and Cognitive Psychology (25 citations), Information Systems (42 citations) and General Social Sciences (5 citations). Pero Subašić has collaborated with scholars based in Serbia, Japan and United States. Frequent co-authors include Alison K. Huettner, Kaoru Hirota, Sanja Vraneš, Benjamin Rey, Rosie Jones, Sayandev Mukherjee and Lin Xiao. Their work appears in journals such as Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Fuzzy Sets and Systems, Expert Systems with Applications and IEEE Transactions on Fuzzy Systems.
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.