Daniel Deutsch
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Text Readability and Simplification
- Speech and dialogue systems
- General Social Sciences top 10%
Papers in
-
- Natural Language Processing Techniques 24
- Topic Modeling 21
- Advanced Text Analysis Techniques 8
- Bayesian Modeling and Causal Inference 2
- Semantic Web and Ontologies 1
- AI-based Problem Solving and Planning 1
-
- Software Engineering Research 4
- Co-authors
- Dan Roth (12 shared papers)Rotem Dror (4 shared papers)Tania Bedrax-Weiss (1 shared paper)Markus Freitag (8 shared papers)Markus Freitag (6 shared papers)John Hewitt (1 shared paper)Jonathan H. Clark (1 shared paper)Ankush Garg (1 shared paper)
- Journals
- Transactions of the Association for Computational Linguistics (2 papers)Journal of the ACM (1 paper)Findings of the Association for Computational Linguistics: ACL 2022 (1 paper)NPARC (1 paper)Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (1 paper)
- Partner nations
- United StatesUnited KingdomPortugal
In The Last Decade
Daniel Deutsch
24 papers receiving 209 citations
Peers
Comparison fields: 5 of 30
- Artificial Intelligence 211
- General Social Sciences 8
- Health Informatics 3
- Computer Vision and Pattern Recognition 35
- Information Systems 23
Countries citing papers authored by Daniel Deutsch
This map shows the geographic impact of Daniel Deutsch'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 Daniel Deutsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Deutsch more than expected).
Fields of papers citing papers by Daniel Deutsch
This network shows the impact of papers produced by Daniel Deutsch. 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 Daniel Deutsch. The network helps show where Daniel Deutsch may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Deutsch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 46 | |
| 2 | 2021 | 35 | |
| 3 | 2023 | 19 | |
| 4 | 2022 | 16 | |
| 5 | 2020 | 14 | |
| 6 | 2022 | 14 | |
| 7 | 2021 | 11 | |
| 8 | 2023 | 10 | |
| 9 | 2023 | 8 | |
| 10 | 2023 | 7 | |
| 11 | 2018 | 7 | |
| 12 | 2019 | 6 | |
| 13 | 2019 | 5 | |
| 14 | 2023 | 4 | |
| 15 | 2023 | 4 | |
| 16 | 2020 | 4 | |
| 17 | 1973 | 4 | |
| 18 | 2023 | 3 | |
| 19 | 2023 | 2 | |
| 20 | 2023 | 2 |
About Daniel Deutsch
Daniel Deutsch is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Information Systems and Management and Computational Theory and Mathematics, having authored 31 papers that have together received 226 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (24 papers), Topic Modeling (21 papers), Advanced Text Analysis Techniques (8 papers), Multimodal Machine Learning Applications (5 papers), Software Engineering Research (4 papers), Bayesian Modeling and Causal Inference (2 papers), Semantic Web and Ontologies (1 paper) and AI-based Problem Solving and Planning (1 paper). The work is most often cited by research in Artificial Intelligence (211 citations), General Social Sciences (8 citations), Health Informatics (3 citations), Computer Vision and Pattern Recognition (35 citations) and Information Systems (23 citations). Daniel Deutsch has collaborated with scholars based in United States, United Kingdom and Portugal. Frequent co-authors include Dan Roth, Rotem Dror, Tania Bedrax-Weiss, Markus Freitag, Markus Freitag, John Hewitt, Jonathan H. Clark, Ankush Garg, Graham Neubig and Patrick Fernandes. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Journal of the ACM, Findings of the Association for Computational Linguistics: ACL 2022, NPARC and Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
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.