Shay B. Cohen
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 5%
- Management Science and Operations Research top 2%
- Information Systems top 5%
- Molecular Biology
- Co-authors
- Shashi NarayanMirella LapataNoah A. SmithYumo XuMarco DamonteAnastasia ShimorinaClaire GardentEytan Ruppin
- Topics
- Topic Modeling (78 papers)Natural Language Processing Techniques (76 papers)Advanced Text Analysis Techniques (12 papers)
- Partner nations
- United KingdomUnited StatesIsrael
In The Last Decade
Shay B. Cohen
110 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Artificial Intelligence 2.0k
- Computer Vision and Pattern Recognition 263
- Management Science and Operations Research 251
- Information Systems 159
- Molecular Biology 148
Countries citing papers authored by Shay B. Cohen
This map shows the geographic impact of Shay B. Cohen'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 Shay B. Cohen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shay B. Cohen more than expected).
Fields of papers citing papers by Shay B. Cohen
This network shows the impact of papers produced by Shay B. Cohen. 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 Shay B. Cohen. The network helps show where Shay B. Cohen may publish in the future.
Co-authorship network of co-authors of Shay B. Cohen
This figure shows the co-authorship network connecting the top 25 collaborators of Shay B. Cohen. A scholar is included among the top collaborators of Shay B. Cohen 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 Shay B. Cohen. Shay B. Cohen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 5 | |
| 8 | 6 | |
| 9 | 4 | |
| 10 | 61 | |
| 11 | Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarizationbreakdown → | 639 |
| 12 | 15 | |
| 13 | Coactive learning for interactive machine translation | 2 |
| 14 | Spectral learning of latent-variable PCFGs: algorithms and sample complexity | 13 |
| 15 | Spectral Learning of Refinement HMMs | 8 |
| 16 | Tensor Decomposition for Fast Parsing with Latent-Variable PCFGs | 21 |
| 17 | Spectral Learning of Latent-Variable PCFGs | 11 |
| 18 | Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing | 12 |
| 19 | Exact Inference for Generative Probabilistic Non-Projective Dependency Parsing | 14 |
| 20 | 15 |
About Shay B. Cohen
Shay B. Cohen is a scholar working on Artificial Intelligence, Computational Mathematics and Health Informatics, having authored 120 papers that have together received 2.4k indexed citations. Recurring topics across this work include Topic Modeling (78 papers), Natural Language Processing Techniques (76 papers) and Advanced Text Analysis Techniques (12 papers). The work is most often cited by research in Artificial Intelligence (2.0k citations), Computational Mathematics (16 citations) and Management Science and Operations Research (251 citations). Shay B. Cohen has collaborated with scholars based in United Kingdom, United States and Israel. Frequent co-authors include Shashi Narayan, Mirella Lapata, Noah A. Smith, Yumo Xu, Marco Damonte, Anastasia Shimorina, Claire Gardent, Eytan Ruppin, Gideon Dror and Giorgio Satta. Their work appears in journals such as PLoS ONE, Solar Energy and Neural Computation.
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.