Amit Somech
Impact in
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing
- Signal Processing top 10%
- Data Management and Algorithms
- Time Series Analysis and Forecasting
Papers in
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- Data Stream Mining Techniques 11
- Machine Learning and Data Classification 6
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- Data Management and Algorithms 7
- Time Series Analysis and Forecasting 6
- Co-authors
- Tova Milo (21 shared papers)Yael Amsterdamer (7 shared papers)Susan B. Davidson (6 shared papers)Slava Novgorodov (3 shared papers)Teddy Lazebnik (2 shared papers)Daniel Deutch (2 shared papers)
- Journals
- Proceedings of the VLDB Endowment (6 papers)Movebank (3 papers)Proceedings of the 2022 International Conference on Management of Data (1 paper)Conference on Innovative Data Systems Research (2 papers)Proceedings of the ACM on Management of Data (1 paper)
- Partner nations
- IsraelUnited StatesUnited Kingdom
In The Last Decade
Amit Somech
23 papers receiving 261 citations
Peers
Comparison fields: 5 of 66
- Computer Science Applications 39
- Signal Processing 63
- Artificial Intelligence 164
- Computer Vision and Pattern Recognition 74
- Information Systems 67
Countries citing papers authored by Amit Somech
This map shows the geographic impact of Amit Somech'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 Amit Somech with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amit Somech more than expected).
Fields of papers citing papers by Amit Somech
This network shows the impact of papers produced by Amit Somech. 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 Amit Somech. The network helps show where Amit Somech may publish in the future.
Co-authors
The 6 scholars most cited alongside Amit Somech, 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 26 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 55 | |
| 2 | 2020 | 44 | |
| 3 | 2018 | 40 | |
| 4 | 2014 | 21 | |
| 5 | 2016 | 16 | |
| 6 | 2022 | 14 | |
| 7 | 2018 | 10 | |
| 8 | Managing General and Individual Knowledge in Crowd Mining Applications | 2015 | 8 |
| 9 | 2022 | 8 | |
| 10 | 2019 | 7 | |
| 11 | 2019 | 7 | |
| 12 | 2020 | 6 | |
| 13 | 2019 | 6 | |
| 14 | 2019 | 4 | |
| 15 | 2014 | 3 | |
| 16 | Towards Autonomous, Hands-Free Data Exploration. | 2020 | 3 |
| 17 | 2023 | 3 | |
| 18 | 2022 | 3 | |
| 19 | 2016 | 2 | |
| 20 | 2022 | 2 |
About Amit Somech
Amit Somech is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 26 papers that have together received 266 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (11 papers), Data Mining Algorithms and Applications (7 papers), Data Management and Algorithms (7 papers), Machine Learning and Data Classification (6 papers), Time Series Analysis and Forecasting (6 papers), Data Visualization and Analytics (5 papers), Advanced Database Systems and Queries (4 papers) and Scientific Computing and Data Management (4 papers). The work is most often cited by research in Computer Science Applications (39 citations), Signal Processing (63 citations), Artificial Intelligence (164 citations), Computer Vision and Pattern Recognition (74 citations) and Information Systems (67 citations). Amit Somech has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Tova Milo, Yael Amsterdamer, Susan B. Davidson, Slava Novgorodov, Teddy Lazebnik and Daniel Deutch. Their work appears in journals such as Proceedings of the VLDB Endowment, Movebank, Proceedings of the 2022 International Conference on Management of Data, Conference on Innovative Data Systems Research and Proceedings of the ACM on Management of Data.
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.