Jonas Sjöbergh
- Artificial Intelligence top 10%
- Safety, Risk, Reliability and Quality top 5%
- Automotive Engineering
- Transportation top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Annika K. JägerbrandViggo KannOla KnutssonKenji ArakiYuzuru TanakaMartin HasselMartin DuneldKeisuke Takahashi
- Topics
- Natural Language Processing Techniques (13 papers)Topic Modeling (11 papers)Data Visualization and Analytics (5 papers)
In The Last Decade
Jonas Sjöbergh
21 papers receiving 225 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 135
- Safety, Risk, Reliability and Quality 68
- Automotive Engineering 33
- Transportation 31
- Computer Vision and Pattern Recognition 28
Countries citing papers authored by Jonas Sjöbergh
This map shows the geographic impact of Jonas Sjöbergh'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 Jonas Sjöbergh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonas Sjöbergh more than expected).
Fields of papers citing papers by Jonas Sjöbergh
This network shows the impact of papers produced by Jonas Sjöbergh. 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 Jonas Sjöbergh. The network helps show where Jonas Sjöbergh may publish in the future.
Co-authorship network of co-authors of Jonas Sjöbergh
This figure shows the co-authorship network connecting the top 25 collaborators of Jonas Sjöbergh. A scholar is included among the top collaborators of Jonas Sjöbergh 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 Jonas Sjöbergh. Jonas Sjöbergh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 5 | |
| 3 | 93 | |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | Navigating Through Summary Space : Selecting Summaries, Not Sentences | 0 |
| 8 | 1 | |
| 9 | What is poorly Said is a Little Funny | 1 |
| 10 | A Complete and Modestly Funny System for Generating and Performing Japanese Stand-Up Comedy | 8 |
| 11 | A Multi-Lingual Dictionary of Dirty Words | 7 |
| 12 | Developing and Evaluating a Searchable Swedish-Thai Lexicon | 0 |
| 13 | 27 | |
| 14 | Vad kan statistik avslöja om svenska sammansättningar | 1 |
| 15 | Towards Holistic Summarization – Selecting Summaries, Not Sentences | 12 |
| 16 | 16 | |
| 17 | Chunking: an unsupervised method to find errors in text | 14 |
| 18 | Grammar checking for Swedish second language learners | 14 |
| 19 | Finding the Correct Interpretation of Swedish Compounds, a Statistical Approach | 21 |
| 20 | Automatic Evaluation of Robustness and Degradation in Tagging and Parsing | 8 |
About Jonas Sjöbergh
Jonas Sjöbergh is a scholar working on Artificial Intelligence, Information Systems and Management and Computer Vision and Pattern Recognition, having authored 23 papers that have together received 256 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (13 papers), Topic Modeling (11 papers) and Data Visualization and Analytics (5 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (68 citations), Transportation (31 citations) and Artificial Intelligence (135 citations). Jonas Sjöbergh has collaborated with scholars based in Japan, Sweden and Canada. Frequent co-authors include Annika K. Jägerbrand, Viggo Kann, Ola Knutsson, Kenji Araki, Yuzuru Tanaka, Martin Hassel, Martin Duneld, Keisuke Takahashi, Eriks Sneiders and Randy Goebel. Their work appears in journals such as Information Processing & Management, Language Resources and Evaluation and SpringerPlus.
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.