Andreas Lommatzsch
- Artificial Intelligence top 5%
- Statistical and Nonlinear Physics top 2%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Jérôme KunegisŞahin AlbayrakErnesto William De LucaStephan SchmidtJürgen LernerChristian BauckhageBenjamin KilleJon Atle Gulla
- Topics
- Recommender Systems and Techniques (11 papers)Topic Modeling (8 papers)Advanced Graph Neural Networks (5 papers)
- Journals
- IEEE AccessInternational Journal of Data Science and AnalyticsScalable Computing Practice and Experience
- Partner nations
- GermanyNorwayUnited States
In The Last Decade
Andreas Lommatzsch
20 papers receiving 498 citations
Peers
Comparison fields: 5 of 69
- Artificial Intelligence 317
- Statistical and Nonlinear Physics 288
- Information Systems 112
- Computer Networks and Communications 68
- Computer Vision and Pattern Recognition 57
Countries citing papers authored by Andreas Lommatzsch
This map shows the geographic impact of Andreas Lommatzsch'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 Andreas Lommatzsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Lommatzsch more than expected).
Fields of papers citing papers by Andreas Lommatzsch
This network shows the impact of papers produced by Andreas Lommatzsch. 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 Andreas Lommatzsch. The network helps show where Andreas Lommatzsch may publish in the future.
Co-authorship network of co-authors of Andreas Lommatzsch
This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Lommatzsch. A scholar is included among the top collaborators of Andreas Lommatzsch 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 Andreas Lommatzsch. Andreas Lommatzsch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | The 2019 Multimedia for Recommender System Task: MovieREC and NewsREEL at MediaEval. | 0 |
| 4 | 7 | |
| 5 | Baseline Algorithms for Predicting the Interest in News Based on Multimedia-Data. | 1 |
| 6 | 85 | |
| 7 | Clicks Pattern Analysis for Online News Recommendation Systems. | 0 |
| 8 | Idomaar: A Framework for Multi-dimensional Benchmarking of Recommender Algorithms | 7 |
| 9 | The potentials of recommender systems challenges for student learning | 1 |
| 10 | 3 | |
| 11 | An Extended Data Model Format for Composite Recommendation | 2 |
| 12 | 4 | |
| 13 | 12 | |
| 14 | Performance measures for multi-graded relevance | 0 |
| 15 | 227 | |
| 16 | Adaptive Music News Recommendations based on Large Semantic Datasets | 1 |
| 17 | From community towards enterprise – a taxonomy-based search for experts | 1 |
| 18 | 121 | |
| 19 | 1 | |
| 20 | 5 |
About Andreas Lommatzsch
Andreas Lommatzsch is a scholar working on Information Systems, Artificial Intelligence and Statistical and Nonlinear Physics, having authored 26 papers that have together received 530 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (11 papers), Topic Modeling (8 papers) and Advanced Graph Neural Networks (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (288 citations), Artificial Intelligence (317 citations) and Computational Mathematics (4 citations). Andreas Lommatzsch has collaborated with scholars based in Germany, Norway and United States. Frequent co-authors include Jérôme Kunegis, Şahin Albayrak, Ernesto William De Luca, Stephan Schmidt, Jürgen Lerner, Christian Bauckhage, Benjamin Kille, Jon Atle Gulla, Roberto Turrin and Özlem Özgöbek. Their work appears in journals such as IEEE Access, International Journal of Data Science and Analytics and Scalable Computing Practice and Experience.
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.