Mark Ferguson
Impact in
- Artificial Intelligence top 2%
- Natural Language Processing Techniques
- Topic Modeling
- Speech and dialogue systems
- Semantic Web and Ontologies
- Text Readability and Simplification
- Advanced Text Analysis Techniques
- Algorithms and Data Compression
- Language and Linguistics top 10%
Papers in
-
- Natural Language Processing Techniques 2
- Semantic Web and Ontologies 2
- Artificial Intelligence in Games 2
- Topic Modeling 2
-
- Visual Attention and Saliency Detection 1
- Co-authors
- Ann Bies (2 shared papers)Karen R. Katz (2 shared papers)Robert B. MacIntyre (2 shared papers)Grace Kim (1 shared paper)Mitchell P. Marcus (1 shared paper)Naim Dahnoun (1 shared paper)Daniel Kudenko⋆ (3 shared papers)Sam Devlin (3 shared papers)
- Journals
- Journal of Visualized Experiments (1 paper)ScholarlyCommons (University of Pennsylvania) (1 paper)Bristol Research (University of Bristol) (1 paper)White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (2 papers)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Mark Ferguson
7 papers receiving 656 citations
Peers
Comparison fields: 5 of 58
- Artificial Intelligence 706
- Language and Linguistics 61
- Information Systems 67
- Computer Vision and Pattern Recognition 53
- Computational Mathematics 1
Countries citing papers authored by Mark Ferguson
This map shows the geographic impact of Mark Ferguson'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 Mark Ferguson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Ferguson more than expected).
Fields of papers citing papers by Mark Ferguson
This network shows the impact of papers produced by Mark Ferguson. 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 Mark Ferguson. The network helps show where Mark Ferguson may publish in the future.
Co-authors
The 23 scholars most cited alongside Mark Ferguson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1994 | 541 | |
| 2 | Bracketing Guidelines For Treebank II Style Penn Treebank Project | 1995 | 220 |
| 3 | 2020 | 3 | |
| 4 | 2022 | 2 | |
| 5 | 2017 | 2 | |
| 6 | Automatic Similarity Detection in LEGO Ducks | 2020 | 1 |
| 7 | 2011 | 1 |
About Mark Ferguson
Mark Ferguson is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Economics and Econometrics, Experimental and Cognitive Psychology and Cancer Research, having authored 7 papers that have together received 770 indexed citations. Recurring topics across this work include Sports Analytics and Performance (2 papers), Natural Language Processing Techniques (2 papers), Semantic Web and Ontologies (2 papers), Artificial Intelligence in Games (2 papers), Topic Modeling (2 papers), Gambling Behavior and Treatments (1 paper), Cancer Genomics and Diagnostics (1 paper) and Visual Attention and Saliency Detection (1 paper). The work is most often cited by research in Artificial Intelligence (706 citations), Language and Linguistics (61 citations), Information Systems (67 citations), Computer Vision and Pattern Recognition (53 citations) and Computational Mathematics (1 citation). Mark Ferguson has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Ann Bies, Karen R. Katz, Robert B. MacIntyre, Grace Kim, Mitchell P. Marcus, Naim Dahnoun, Daniel Kudenko⋆, Sam Devlin, James Alfred Walker and Fabio Méndez. Their work appears in journals such as Journal of Visualized Experiments, ScholarlyCommons (University of Pennsylvania), Bristol Research (University of Bristol) and White Rose Research Online (University of Leeds, The University of Sheffield, University of York).
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.