Christoph Freudenthaler

9.1k total citations · 2 hit papers
18 papers, 2.9k citations indexed

About

Christoph Freudenthaler is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Christoph Freudenthaler has authored 18 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Information Systems, 10 papers in Artificial Intelligence and 9 papers in Management Science and Operations Research. Recurrent topics in Christoph Freudenthaler's work include Recommender Systems and Techniques (14 papers), Advanced Bandit Algorithms Research (9 papers) and Machine Learning and Algorithms (5 papers). Christoph Freudenthaler is often cited by papers focused on Recommender Systems and Techniques (14 papers), Advanced Bandit Algorithms Research (9 papers) and Machine Learning and Algorithms (5 papers). Christoph Freudenthaler collaborates with scholars based in Germany, Austria and Netherlands. Christoph Freudenthaler's co-authors include Steffen Rendle, Lars Schmidt-Thieme, Zeno Gantner, Lucas Drumond, Artus Krohn-Grimberghe, Αλέξανδρος Νανόπουλος, René Böheim, George Psihoyios, Ch. Tsitouras and Theodore E. Simos and has published in prestigious journals such as Labour Economics, Knowledge Discovery and Data Mining and International Joint Conference on Artificial Intelligence.

In The Last Decade

Christoph Freudenthaler

15 papers receiving 2.9k citations

Hit Papers

Factorizing personalized Markov chains for next-basket re... 2010 2026 2015 2020 2010 2011 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Factorizing personalized Markov chains for next-basket recommendation
    2010 1.6k citations Steffen Rendle, Christoph Freudenthaler et al. profile →
  2. Fast context-aware recommendations with factorization machines
    2011 376 citations Steffen Rendle, Zeno Gantner et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Christoph Freudenthaler Germany 12 2.6k 1.6k 763 721 412 18 2.9k
Linas Baltrunas Spain 19 2.0k 0.8× 854 0.5× 717 0.9× 459 0.6× 355 0.9× 31 2.4k
Abraham Gutiérrez Spain 11 2.0k 0.8× 1.0k 0.6× 695 0.9× 374 0.5× 208 0.5× 41 2.5k
Guibing Guo China 26 2.1k 0.8× 1.4k 0.9× 577 0.8× 374 0.5× 172 0.4× 91 2.5k
Alejandro Bellogín Spain 27 1.5k 0.6× 894 0.5× 396 0.5× 407 0.6× 150 0.4× 95 1.9k
Xiaoqiang Zhu China 8 1.8k 0.7× 1.3k 0.8× 823 1.1× 453 0.6× 137 0.3× 15 2.3k
Xiuqiang He China 27 1.7k 0.7× 1.6k 1.0× 744 1.0× 463 0.6× 130 0.3× 99 2.5k
Al Borchers United States 7 2.0k 0.8× 794 0.5× 696 0.9× 352 0.5× 148 0.4× 11 2.5k
Zhaochun Ren China 33 2.2k 0.8× 3.1k 1.9× 731 1.0× 455 0.6× 106 0.3× 147 3.9k
Wenwu Ou China 16 1.6k 0.6× 1.3k 0.8× 546 0.7× 454 0.6× 110 0.3× 30 2.1k

Countries citing papers authored by Christoph Freudenthaler

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Christoph Freudenthaler

This figure shows the co-authorship network connecting the top 25 collaborators of Christoph Freudenthaler. A scholar is included among the top collaborators of Christoph Freudenthaler 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 Christoph Freudenthaler. Christoph Freudenthaler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
1.
Böheim, René, et al.. (2025). Male coaches increase the risk-taking of female teams—Evidence from the NCAA. Labour Economics. 94. 102692–102692.
2.
Böheim, René, et al.. (2019). Do Male Managers Increase Risk-Taking of Female Teams? Evidence from the NCAA. SSRN Electronic Journal.
3.
Böheim, René, et al.. (2016). Gender Differences in Risk-Taking: Evidence from Professional Basketball. SSRN Electronic Journal. 8 indexed citations
4.
Freudenthaler, Christoph, et al.. (2015). Comparing Prediction Models for Active Learning in Recommender Systems.. LWA. 171–180. 1 indexed citations
5.
Rendle, Steffen & Christoph Freudenthaler. (2014). Improving pairwise learning for item recommendation from implicit feedback. 273–282. 249 indexed citations
6.
Krohn-Grimberghe, Artus, Lucas Drumond, Christoph Freudenthaler, & Lars Schmidt-Thieme. (2012). Multi-relational matrix factorization using bayesian personalized ranking for social network data. 173–182. 137 indexed citations
7.
Freudenthaler, Christoph, et al.. (2012). Exploiting the characteristics of matrix factorization for active learning in recommender systems. 317–320. 15 indexed citations
8.
Gantner, Zeno, Lucas Drumond, Christoph Freudenthaler, & Lars Schmidt-Thieme. (2011). Personalized Ranking for non-uniformly sampled items. Knowledge Discovery and Data Mining. 231–247. 37 indexed citations
9.
Wartena, Christian, et al.. (2011). Keyword-Based TV Program Recommendation.. International Joint Conference on Artificial Intelligence. 45(6). 869–77.
10.
Gantner, Zeno, Lucas Drumond, Christoph Freudenthaler, & Lars Schmidt-Thieme. (2011). Bayesian Personalized Ranking for Non-Uniformly Sampled Items. 15 indexed citations
11.
Rendle, Steffen, Zeno Gantner, Christoph Freudenthaler, & Lars Schmidt-Thieme. (2011). Fast context-aware recommendations with factorization machines. 635–644. 376 indexed citations breakdown →
12.
Freudenthaler, Christoph, et al.. (2011). Non-myopic active learning for recommender systems based on Matrix Factorization. 22 indexed citations
13.
Gantner, Zeno, Steffen Rendle, Christoph Freudenthaler, & Lars Schmidt-Thieme. (2011). MyMediaLite. 305–308. 260 indexed citations
14.
Freudenthaler, Christoph, Steffen Rendle, Lars Schmidt-Thieme, et al.. (2011). Factorizing Markov Models for Categorical Time Series Prediction. AIP conference proceedings. 405–409. 1 indexed citations
15.
Freudenthaler, Christoph, et al.. (2011). Active learning for aspect model in recommender systems. 162–167. 14 indexed citations
16.
Freudenthaler, Christoph, et al.. (2011). Towards Optimal Active Learning for Matrix Factorization in Recommender Systems. 1069–1076. 16 indexed citations
17.
Gantner, Zeno, Lucas Drumond, Christoph Freudenthaler, Steffen Rendle, & Lars Schmidt-Thieme. (2010). Learning Attribute-to-Feature Mappings for Cold-Start Recommendations. 176–185. 194 indexed citations
18.
Rendle, Steffen, Christoph Freudenthaler, & Lars Schmidt-Thieme. (2010). Factorizing personalized Markov chains for next-basket recommendation. 811–820. 1597 indexed citations breakdown →

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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