Marko Tkalčič
Impact in
- Information Systems top 1%
- Recommender Systems and Techniques
- Signal Processing top 2%
- Music and Audio Processing
Papers in
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- Video Analysis and Summarization 24
- Image Retrieval and Classification Techniques 13
- Music Technology and Sound Studies 10
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- Recommender Systems and Techniques 38
- Co-authors
- J.F. Tasič (14 shared papers)Bruce Ferwerda (27 shared papers)Markus Schedl (27 shared papers)Andrej Košir (25 shared papers)Ante Odić (16 shared papers)Alexander Felfernig (11 shared papers)Martin Stettinger (10 shared papers)Ludovico Boratto (10 shared papers)
In The Last Decade
Marko Tkalčič
110 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 135
- Information Systems 886
- Signal Processing 388
- Computer Vision and Pattern Recognition 680
- Computational Mathematics 14
- Marketing 173
Countries citing papers authored by Marko Tkalčič
This map shows the geographic impact of Marko Tkalčič'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 Marko Tkalčič with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marko Tkalčič more than expected).
Fields of papers citing papers by Marko Tkalčič
This network shows the impact of papers produced by Marko Tkalčič. 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 Marko Tkalčič. The network helps show where Marko Tkalčič may publish in the future.
Co-authors
The 25 scholars most cited alongside Marko Tkalčič, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 118 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 252 | |
| 2 | 2016 | 98 | |
| 3 | 2013 | 89 | |
| 4 | 2010 | 82 | |
| 5 | 2013 | 79 | |
| 6 | 2015 | 79 | |
| 7 | Database for contextual personalization | 2011 | 78 |
| 8 | 2015 | 65 | |
| 9 | 2016 | 64 | |
| 10 | 2012 | 62 | |
| 11 | Personality Based User Similarity Measure for a Collaborative Recommender System | 2009 | 60 |
| 12 | 2015 | 58 | |
| 13 | Relevant Context in a Movie Recommender System: Users' Opinion vs. Statistical Detection | 2012 | 57 |
| 14 | 2018 | 57 | |
| 15 | 2016 | 55 | |
| 16 | 2018 | 54 | |
| 17 | 2018 | 46 | |
| 18 | 2017 | 41 | |
| 19 | Addressing the New User Problem with a Personality Based User Similarity Measure | 2011 | 36 |
| 20 | 2013 | 36 |
About Marko Tkalčič
Marko Tkalčič is a scholar working on Computer Vision and Pattern Recognition, Information Systems, Signal Processing, Artificial Intelligence and Cognitive Neuroscience, having authored 118 papers that have together received 2.2k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (38 papers), Music and Audio Processing (30 papers), Video Analysis and Summarization (24 papers), Neuroscience and Music Perception (16 papers), Personality Traits and Psychology (13 papers), Media Influence and Health (13 papers), Image Retrieval and Classification Techniques (13 papers) and Music Technology and Sound Studies (10 papers). The work is most often cited by research in Information Systems (886 citations), Signal Processing (388 citations), Computer Vision and Pattern Recognition (680 citations), Computational Mathematics (14 citations) and Marketing (173 citations). Marko Tkalčič has collaborated with scholars based in Slovenia, Austria and Italy. Frequent co-authors include J.F. Tasič, Bruce Ferwerda, Markus Schedl, Andrej Košir, Ante Odić, Alexander Felfernig, Martin Stettinger, Ludovico Boratto, Li Chen and Berardina De Carolis. Their work appears in journals such as User Modeling and User-Adapted Interaction, Multimedia Tools and Applications, Information Processing & Management, IEEE Transactions on Affective Computing and IEEE Transactions on Multimedia.
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.