Christoph Freudenthaler
- Information Systems top 0.1%
- Recommender Systems and Techniques 14
- Computational Mathematics top 2%
- Tensor decomposition and applications 2
- Transportation top 1%
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- Advanced Bandit Algorithms Research 9
- Artificial Intelligence top 0.5%
- Machine Learning and Algorithms 5
- Advanced Graph Neural Networks 2
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- Sports Analytics and Performance 5
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- Sport and Mega-Event Impacts 3
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- Sports, Gender, and Society 2
- Co-authors
- Steffen RendleLars Schmidt-ThiemeZeno GantnerLucas DrumondArtus Krohn-GrimbergheΑλέξανδρος ΝανόπουλοςRené BöheimCh. Tsitouras
- Partner nations
- GermanyAustriaNetherlands
In The Last Decade
Christoph Freudenthaler
15 papers receiving 2.9k citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Information Systems 2.6k
- Computational Mathematics 59
- Transportation 412
- Management Science and Operations Research 721
- Artificial Intelligence 1.6k
Countries citing papers authored by Christoph Freudenthaler
This map shows the geographic impact of Christoph Freudenthaler'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 Christoph Freudenthaler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christoph Freudenthaler more than expected).
Fields of papers citing papers by Christoph Freudenthaler
This network shows the impact of papers produced by Christoph Freudenthaler. 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 Christoph Freudenthaler. The network helps show where Christoph Freudenthaler may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Christoph Freudenthaler, 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 | 2025 | 0 | |
| 2 | 2019 | 0 | |
| 3 | 2016 | 8 | |
| 4 | Comparing Prediction Models for Active Learning in Recommender Systems. | 2015 | 1 |
| 5 | 2014 | 249 | |
| 6 | 2012 | 15 | |
| 7 | 2012 | 137 | |
| 8 | 2011 | 0 | |
| 9 | Personalized Ranking for non-uniformly sampled items | 2011 | 37 |
| 10 | Fast context-aware recommendations with factorization machinesbreakdown → | 2011 | 376 |
| 11 | Bayesian Personalized Ranking for Non-Uniformly Sampled Items | 2011 | 15 |
| 12 | 2011 | 22 | |
| 13 | 2011 | 1 | |
| 14 | 2011 | 260 | |
| 15 | 2011 | 14 | |
| 16 | 2011 | 16 | |
| 17 | 2010 | 194 | |
| 18 | Factorizing personalized Markov chains for next-basket recommendationbreakdown → | 2010 | 1597 |
About Christoph Freudenthaler
Christoph Freudenthaler is a scholar working on Computational Mathematics, Management Science and Operations Research and Information Systems, having authored 18 papers that have together received 2.9k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (14 papers), Advanced Bandit Algorithms Research (9 papers), Machine Learning and Algorithms (5 papers), Sports Analytics and Performance (5 papers), Sport and Mega-Event Impacts (3 papers), Tensor decomposition and applications (2 papers), Sports, Gender, and Society (2 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Information Systems (2.6k citations), Computational Mathematics (59 citations) and Transportation (412 citations). Christoph Freudenthaler has collaborated with scholars based in Germany, Austria and Netherlands. Frequent co-authors include Steffen Rendle, Lars Schmidt-Thieme, Zeno Gantner, Lucas Drumond, Artus Krohn-Grimberghe, Αλέξανδρος Νανόπουλος, René Böheim, Ch. Tsitouras, Zacharias Anastassi and Theodore E. Simos.
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.