Joel Nothman
- Artificial Intelligence top 1%
- Management Science and Operations Research top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Communication top 5%
- Co-authors
- James CurranTara MurphyWill RadfordBen HacheyNicky RinglandHeng JiMatthew HonnibalBoliang Zhang
- Topics
- Natural Language Processing Techniques (26 papers)Topic Modeling (24 papers)Data Quality and Management (9 papers)
- Partner nations
- AustraliaUnited StatesChina
In The Last Decade
Joel Nothman
30 papers receiving 852 citations
Peers
Comparison fields: 5 of 70
- Artificial Intelligence 893
- Management Science and Operations Research 169
- Information Systems 123
- Computer Vision and Pattern Recognition 96
- Communication 82
Countries citing papers authored by Joel Nothman
This map shows the geographic impact of Joel Nothman'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 Joel Nothman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joel Nothman more than expected).
Fields of papers citing papers by Joel Nothman
This network shows the impact of papers produced by Joel Nothman. 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 Joel Nothman. The network helps show where Joel Nothman may publish in the future.
Co-authorship network of co-authors of Joel Nothman
This figure shows the co-authorship network connecting the top 25 collaborators of Joel Nothman. A scholar is included among the top collaborators of Joel Nothman 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 Joel Nothman. Joel Nothman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | Overview of TAC-KBP 2019 Fine-grained Entity Extraction. | 2 |
| 3 | 29 | |
| 4 | 202 | |
| 5 | Overview of TAC-KBP2017 13 Languages Entity Discovery and Linking. | 21 |
| 6 | 8 | |
| 7 | Overview of TAC-KBP2016 Tri-lingual EDL and Its Impact on End-to-End KBP. | 10 |
| 8 | Overview of TAC-KBP2015 Tri-lingual Entity Discovery and Linking. | 55 |
| 9 | 3 | |
| 10 | Unsupervised Biographical Event Extraction Using Wikipedia Traffic | 2 |
| 11 | Trading accuracy for faster named entity linking | 1 |
| 12 | 4 | |
| 13 | SYDNEY CMCRC at TAC 2013. | 4 |
| 14 | Event Linking: Grounding Event Reference in a News Archive | 17 |
| 15 | (Almost) Total Recall - SYDNEY CMCRC at TAC 2012. | 8 |
| 16 | 155 | |
| 17 | 207 | |
| 18 | 9 | |
| 19 | Transforming Wikipedia into Named Entity Training Data | 57 |
| 20 | Learning Named Entity Recognition from Wikipedia | 8 |
About Joel Nothman
Joel Nothman is a scholar working on Artificial Intelligence, Management Science and Operations Research and Communication, having authored 30 papers that have together received 969 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (26 papers), Topic Modeling (24 papers) and Data Quality and Management (9 papers). The work is most often cited by research in Artificial Intelligence (893 citations), Management Science and Operations Research (169 citations) and Communication (82 citations). Joel Nothman has collaborated with scholars based in Australia, United States and China. Frequent co-authors include James Curran, Tara Murphy, Will Radford, Ben Hachey, Nicky Ringland, Heng Ji, Matthew Honnibal, Boliang Zhang, Xiaoman Pan and Kevin Knight. Their work appears in journals such as Artificial Intelligence, JMIR mhealth and uhealth and Theory and applications of categories.
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.