Johannes Hoffart
- Artificial Intelligence top 1%
- Information Systems top 2%
- Management Science and Operations Research top 2%
- Signal Processing top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Gerhard WeikumFabian M. SuchanekKlaus BerberichMartin TheobaldDat Ba NguyenGerard de MeloStephan SeufertYasemin Altün
- Topics
- Topic Modeling (17 papers)Semantic Web and Ontologies (13 papers)Natural Language Processing Techniques (11 papers)
- Partner nations
- GermanyUnited StatesAustria
In The Last Decade
Johannes Hoffart
26 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 1.2k
- Information Systems 358
- Management Science and Operations Research 293
- Signal Processing 152
- Computer Networks and Communications 144
Countries citing papers authored by Johannes Hoffart
This map shows the geographic impact of Johannes Hoffart'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 Johannes Hoffart with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Johannes Hoffart more than expected).
Fields of papers citing papers by Johannes Hoffart
This network shows the impact of papers produced by Johannes Hoffart. 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 Johannes Hoffart. The network helps show where Johannes Hoffart may publish in the future.
Co-authorship network of co-authors of Johannes Hoffart
This figure shows the co-authorship network connecting the top 25 collaborators of Johannes Hoffart. A scholar is included among the top collaborators of Johannes Hoffart 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 Johannes Hoffart. Johannes Hoffart is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 15 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 30 | |
| 8 | 14 | |
| 9 | 13 | |
| 10 | 33 | |
| 11 | 4 | |
| 12 | YAGO2: a spatially and temporally enhanced knowledge base from wikipedia (extended abstract) | 12 |
| 13 | Crowdsourced entity markup | 8 |
| 14 | 1 | |
| 15 | YAGO2s: Modular High-quality Information Extraction with an Application to Flight Planning | 9 |
| 16 | 5 | |
| 17 | YAGO2: A spatially and temporally enhanced knowledge base from Wikipediabreakdown → | 745 |
| 18 | 126 | |
| 19 | 85 | |
| 20 | 5 |
About Johannes Hoffart
Johannes Hoffart is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Science Applications, having authored 26 papers that have together received 1.4k indexed citations. Recurring topics across this work include Topic Modeling (17 papers), Semantic Web and Ontologies (13 papers) and Natural Language Processing Techniques (11 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Management Science and Operations Research (293 citations) and Information Systems (358 citations). Johannes Hoffart has collaborated with scholars based in Germany, United States and Austria. Frequent co-authors include Gerhard Weikum, Fabian M. Suchanek, Klaus Berberich, Martin Theobald, Dat Ba Nguyen, Gerard de Melo, Stephan Seufert, Yasemin Altün, Mohamed Amir Yosef and Marc Spaniol. Their work appears in journals such as Artificial Intelligence, Proceedings of the VLDB Endowment and KI - Künstliche Intelligenz.
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.