Rainer Gemulla
- Computational Mathematics top 2%
- Artificial Intelligence top 1%
- Topic Modeling 17
- Advanced Graph Neural Networks 11
- Natural Language Processing Techniques 10
- Algorithms and Data Compression 9
- Data Stream Mining Techniques 6
- Information Systems top 0.5%
- Data Mining Algorithms and Applications 7
- Signal Processing top 2%
- Data Management and Algorithms 12
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- Advanced Database Systems and Queries 14
- Co-authors
- Peter J. HaasLuciano Del CorroYannis SismanisErik NijkampWolfgang LehnerKevin BeyerJohn McPhersonMohamed Y. Eltabakh
- Journals
- Proceedings of the VLDB Endowment (7 papers)ACM Transactions on Database Systems (3 papers)The VLDB Journal (2 papers)
- Partner nations
- GermanyUnited StatesAustralia
In The Last Decade
Rainer Gemulla
54 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 89
- Computational Mathematics 45
- Artificial Intelligence 1.3k
- Information Systems 841
- Signal Processing 361
- Computer Networks and Communications 752
Countries citing papers authored by Rainer Gemulla
This map shows the geographic impact of Rainer Gemulla'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 Rainer Gemulla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rainer Gemulla more than expected).
Fields of papers citing papers by Rainer Gemulla
This network shows the impact of papers produced by Rainer Gemulla. 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 Rainer Gemulla. The network helps show where Rainer Gemulla may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Rainer Gemulla, 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 | 1 | |
| 2 | 2023 | 4 | |
| 3 | 2022 | 73 | |
| 4 | 2022 | 11 | |
| 5 | 2021 | 13 | |
| 6 | 2020 | 14 | |
| 7 | You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings | 2020 | 44 |
| 8 | 2020 | 34 | |
| 9 | 2019 | 5 | |
| 10 | 2018 | 6 | |
| 11 | 2017 | 87 | |
| 12 | 2015 | 16 | |
| 13 | Robust Principal Component Analysis as a Nonlinear Eigenproblem | 2013 | 1 |
| 14 | A Weakly Supervised Model for Sentence-Level Semantic Orientation Analysis with Multiple Experts | 2012 | 14 |
| 15 | CoHadoop: Flexible Data Placement and Its Exploitation in Hadoop 1 | 2011 | 11 |
| 16 | 2010 | 42 | |
| 17 | 2009 | 38 | |
| 18 | 2007 | 128 | |
| 19 | 2007 | 31 | |
| 20 | 2006 | 29 |
About Rainer Gemulla
Rainer Gemulla is a scholar working on Artificial Intelligence, Signal Processing, Computer Networks and Communications, Information Systems and Computational Theory and Mathematics, having authored 56 papers that have together received 2.1k indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Advanced Database Systems and Queries (14 papers), Data Management and Algorithms (12 papers), Advanced Graph Neural Networks (11 papers), Natural Language Processing Techniques (10 papers), Algorithms and Data Compression (9 papers), Data Mining Algorithms and Applications (7 papers) and Data Stream Mining Techniques (6 papers). The work is most often cited by research in Computational Mathematics (45 citations), Artificial Intelligence (1.3k citations), Information Systems (841 citations), Signal Processing (361 citations) and Computer Networks and Communications (752 citations). Rainer Gemulla has collaborated with scholars based in Germany, United States and Australia. Frequent co-authors include Peter J. Haas, Luciano Del Corro, Yannis Sismanis, Erik Nijkamp, Wolfgang Lehner, Kevin Beyer, John McPherson, Mohamed Y. Eltabakh, Christina Teflioudi and Fatma Özcan. Their work appears in journals such as Proceedings of the VLDB Endowment, ACM Transactions on Database Systems, The VLDB Journal, Communications of the ACM and Transactions of the Association for Computational Linguistics.
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.