Giannis Karamanolakis
- Artificial Intelligence
- Information Systems
- Computer Vision and Pattern Recognition
- Signal Processing
- Social Psychology
- Co-authors
- Daniel HsuLuis GravanoAhmed Hassan AwadallahGuo‐qing ZhengSubhabrata MukherjeeDa TangJie YuanTony Jebara
- Topics
- Topic Modeling (4 papers)Advanced Text Analysis Techniques (3 papers)Text and Document Classification Technologies (2 papers)
- Journals
- Transactions of the Association for Computational LinguisticsProceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Giannis Karamanolakis
6 papers receiving 94 citations
Peers
Comparison fields: 5 of 36
- Artificial Intelligence 73
- Information Systems 30
- Computer Vision and Pattern Recognition 18
- Signal Processing 8
- Social Psychology 6
Countries citing papers authored by Giannis Karamanolakis
This map shows the geographic impact of Giannis Karamanolakis'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 Giannis Karamanolakis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Giannis Karamanolakis more than expected).
Fields of papers citing papers by Giannis Karamanolakis
This network shows the impact of papers produced by Giannis Karamanolakis. 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 Giannis Karamanolakis. The network helps show where Giannis Karamanolakis may publish in the future.
Co-authorship network of co-authors of Giannis Karamanolakis
This figure shows the co-authorship network connecting the top 25 collaborators of Giannis Karamanolakis. A scholar is included among the top collaborators of Giannis Karamanolakis 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 Giannis Karamanolakis. Giannis Karamanolakis 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 | 1 | |
| 3 | 36 | |
| 4 | 6 | |
| 5 | Training Neural Networks for Aspect Extraction Using Descriptive Keywords Only | 2 |
| 6 | 24 | |
| 7 | 28 | |
| 8 | 0 |
About Giannis Karamanolakis
Giannis Karamanolakis is a scholar working on Artificial Intelligence, Cultural Studies and Signal Processing, having authored 8 papers that have together received 97 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Advanced Text Analysis Techniques (3 papers) and Text and Document Classification Technologies (2 papers). The work is most often cited by research in Artificial Intelligence (73 citations), Information Systems (30 citations) and Computer Vision and Pattern Recognition (18 citations). Giannis Karamanolakis has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Daniel Hsu, Luis Gravano, Ahmed Hassan Awadallah, Guo‐qing Zheng, Subhabrata Mukherjee, Da Tang, Jie Yuan, Tony Jebara, Elias Iosif and Aggelos Pikrakis. Their work appears in journals such as Transactions of the Association for Computational Linguistics 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.