Tanja Urbančič

725 total citations
34 papers, 365 citations indexed

About

Tanja Urbančič is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Tanja Urbančič has authored 34 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 7 papers in Molecular Biology and 6 papers in Information Systems. Recurrent topics in Tanja Urbančič's work include Biomedical Text Mining and Ontologies (6 papers), AI-based Problem Solving and Planning (5 papers) and Machine Learning in Bioinformatics (3 papers). Tanja Urbančič is often cited by papers focused on Biomedical Text Mining and Ontologies (6 papers), AI-based Problem Solving and Planning (5 papers) and Machine Learning in Bioinformatics (3 papers). Tanja Urbančič collaborates with scholars based in Slovenia, Australia and Netherlands. Tanja Urbančič's co-authors include Bogdan Filipič, Ivan Bratko, Bojan Cestnik, Nada Lavrač, Marko Bohanec, Claude Sammut, Maarten van Someren, Peter Flach, Senja Pollak and Đani Juričić and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Engineering Applications of Artificial Intelligence.

In The Last Decade

Tanja Urbančič

32 papers receiving 318 citations

Peers

Tanja Urbančič
Comparison fields: 5 of 90
  • Artificial Intelligence 177
  • Control and Systems Engineering 131
  • Molecular Biology 35
  • Electrical and Electronic Engineering 32
  • Computational Theory and Mathematics 22
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Citations per field, relative to Tanja Urbančič
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Citations per year, relative to Tanja Urbančič
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Countries citing papers authored by Tanja Urbančič

Since Specialization
Citations

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

Fields of papers citing papers by Tanja Urbančič

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tanja Urbančič

This figure shows the co-authorship network connecting the top 25 collaborators of Tanja Urbančič. A scholar is included among the top collaborators of Tanja Urbančič 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 Tanja Urbančič. Tanja Urbančič 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
# Work Indexed citations
1 2
2 1
3 7
4
Optimality Principles in Computational Approaches to Conceptual Blending: Do We Need Them (at) All?
4
5
The Good, the Bad, and the AHA! Blends.
5
6
Automated Blend Naming Based on Human Creativity Examples.
1
7 2
8
Cross-domain literature mining: Finding bridging concepts with CrossBee.
8
9 1
10
From Fragments of Knowledge Towards a Bigger Picture: How Can the Process be Supported
4
11
Structuring Domain Knowledge by Semi-automatic Ontology Construction
2
12
Discovering Hidden Knowledge from Biomedical Literature
13
13 5
14
Web-based analysis of data mining and decision support education
8
15 14
16
Learning to control dynamic systems
12
17 22
18
Reconstructing human skill with machine learning
32
19 7
20
Varying levels of abstraction in qualitative modeling
1

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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