Lars Schmidt-Thieme
Impact in
- Computational Mathematics top 0.2%
- Information Systems top 0.05%
- Recommender Systems and Techniques
Papers in
-
- Recommender Systems and Techniques 51
- Co-authors
- Steffen RendleChristoph FreudenthalerZeno GantnerNguyen Thai-NgheLucas DrumondLeandro Balby MarinhoMartin WistubaNicolas Schilling
In The Last Decade
Lars Schmidt-Thieme
149 papers receiving 6.2k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Computational Mathematics 296
- Information Systems 4.2k
- Artificial Intelligence 3.6k
- Computer Science Applications 516
- Transportation 547
Countries citing papers authored by Lars Schmidt-Thieme
This map shows the geographic impact of Lars Schmidt-Thieme'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 Lars Schmidt-Thieme with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lars Schmidt-Thieme more than expected).
Fields of papers citing papers by Lars Schmidt-Thieme
This network shows the impact of papers produced by Lars Schmidt-Thieme. 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 Lars Schmidt-Thieme. The network helps show where Lars Schmidt-Thieme may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Lars Schmidt-Thieme, 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 | 2023 | 6 | |
| 2 | 2023 | 3 | |
| 3 | Matrix Factorization for Near Real-time Geolocation Prediction in Twitter Stream. | 2016 | 1 |
| 4 | 2016 | 7 | |
| 5 | Geo_ML @ MediaEval Placing Task 2015 | 2015 | 1 |
| 6 | A Transfer Learning Approach for Applying Matrix Factorization to Small ITS Datasets. | 2015 | 4 |
| 7 | Comparing Prediction Models for Active Learning in Recommender Systems. | 2015 | 1 |
| 8 | Improved Questionnaire Trees for Active Learning in Recommender Systems. | 2014 | 3 |
| 9 | Matrix Factorization Feasibility for Sequencing and Adaptive Support in Intelligent Tutoring Systems | 2014 | 3 |
| 10 | Supervised Clustering of Social Media Streams. | 2013 | 7 |
| 11 | Using factorization machines for student modeling. | 2012 | 16 |
| 12 | Information extraction from ultrawideband ground penetrating radar data: A machine learning approach | 2012 | 12 |
| 13 | Factorization techniques for student performance classification and ranking. | 2012 | 2 |
| 14 | 2011 | 0 | |
| 15 | Factor models for tag recommendation in bibsonomy | 2009 | 21 |
| 16 | Data Analysis, Machine Learning and Applications: Proceedings of the 31st Annual Conference of the Gesellschaft fr Klassifikation e.V., Albert-Ludwigs-Universitt ... Data Analysis, and Knowledge Organization) | 2008 | 2 |
| 17 | Proceedings of the third ACM conference on Recommender systems | 2008 | 6 |
| 18 | Data Analysis and Decision Support (Studies in Classification, Data Analysis, and Knowledge Organization) | 2005 | 6 |
| 19 | Collaborative and Usage-driven Evolution of Personal Ontologies. | 2005 | 5 |
| 20 | Die formale Gestaltung von Exposition und Reprise in den Streichquartetten Haydns | 2000 | 3 |
About Lars Schmidt-Thieme
Lars Schmidt-Thieme is a scholar working on Computational Mathematics, Information Systems, Artificial Intelligence, Computer Science Applications and Signal Processing, having authored 156 papers that have together received 6.5k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (51 papers), Intelligent Tutoring Systems and Adaptive Learning (19 papers), Time Series Analysis and Forecasting (18 papers), Advanced Bandit Algorithms Research (15 papers), Topic Modeling (13 papers), Machine Learning and Data Classification (13 papers), Text and Document Classification Technologies (13 papers) and Online Learning and Analytics (12 papers). The work is most often cited by research in Computational Mathematics (296 citations), Information Systems (4.2k citations), Artificial Intelligence (3.6k citations), Computer Science Applications (516 citations) and Transportation (547 citations). Lars Schmidt-Thieme has collaborated with scholars based in Germany, Hungary and Slovakia. Frequent co-authors include Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, Nguyen Thai-Nghe, Lucas Drumond, Leandro Balby Marinho, Martin Wistuba, Nicolas Schilling, Josif Grabocka and Αλέξανδρος Νανόπουλος. Their work appears in journals such as Knowledge and Information Systems, Data Mining and Knowledge Discovery, Computer Networks, Biochemical Engineering Journal and Language Resources and Evaluation.
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.