Dan Klein
- Artificial Intelligence top 0.02%
- Natural Language Processing Techniques 144
- Topic Modeling 137
- Speech and dialogue systems 35
- Algorithms and Data Compression 23
- Text Readability and Simplification 18
- Speech Recognition and Synthesis 17
- Machine Learning and Algorithms 11
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- Multimodal Machine Learning Applications 19
- Information Systems top 0.2%
- Signal Processing top 1%
- Software top 5%
- Co-authors
- Christopher D. ManningPercy LiangSlav PetrovKristina ToutanovaYoram SingerAria HaghighiMichael I. JordanTaylor Berg-Kirkpatrick
- Journals
- Transactions of the Association for Computational Linguistics (2 papers)Computational Linguistics (1 paper)Pattern Recognition (1 paper)
- Partner nations
- United StatesAustraliaIsrael
In The Last Decade
Dan Klein
190 papers receiving 12.5k citations
Hit Papers
Peers
Comparison fields: 5 of 150
- Artificial Intelligence 12.5k
- Computer Vision and Pattern Recognition 2.2k
- Information Systems 1.6k
- Signal Processing 562
- Software 154
Countries citing papers authored by Dan Klein
This map shows the geographic impact of Dan Klein'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 Dan Klein with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Klein more than expected).
Fields of papers citing papers by Dan Klein
This network shows the impact of papers produced by Dan Klein. 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 Dan Klein. The network helps show where Dan Klein may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dan Klein, 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 | 2024 | 11 | |
| 2 | 2023 | 0 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 4 | |
| 6 | 2023 | 8 | |
| 7 | 2021 | 35 | |
| 8 | 2020 | 37 | |
| 9 | 2016 | 234 | |
| 10 | 2013 | 115 | |
| 11 | 2013 | 8 | |
| 12 | 2013 | 14 | |
| 13 | An Empirical Examination of Challenges in Chinese Parsing | 2013 | 11 |
| 14 | Coreference Semantics from Web Features | 2012 | 27 |
| 15 | Jointly Learning to Extract and Compress | 2011 | 122 |
| 16 | Simple Effective Decipherment via Combinatorial Optimization | 2011 | 10 |
| 17 | Top-Down K-Best A* Parsing | 2010 | 5 |
| 18 | 2008 | 3 | |
| 19 | 2005 | 78 | |
| 20 | Parsing and Hypergraphs | 2001 | 70 |
About Dan Klein
Dan Klein is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cultural Studies, having authored 197 papers that have together received 14.0k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (144 papers), Topic Modeling (137 papers), Speech and dialogue systems (35 papers), Algorithms and Data Compression (23 papers), Multimodal Machine Learning Applications (19 papers), Text Readability and Simplification (18 papers), Speech Recognition and Synthesis (17 papers) and Machine Learning and Algorithms (11 papers). The work is most often cited by research in Artificial Intelligence (12.5k citations), Computer Vision and Pattern Recognition (2.2k citations) and Information Systems (1.6k citations). Dan Klein has collaborated with scholars based in United States, Australia and Israel. Frequent co-authors include Christopher D. Manning, Percy Liang, Slav Petrov, Kristina Toutanova, Yoram Singer, Aria Haghighi, Michael I. Jordan, Taylor Berg-Kirkpatrick, Ben Taskar and Sepandar Kamvar. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Computational Linguistics, Pattern Recognition, Cognitive Science and Proceedings of the National Academy of Sciences.
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.