Mark Law
Impact in
- Artificial Intelligence top 10%
- Logic, Reasoning, and Knowledge
- Privacy-Preserving Technologies in Data
- Multi-Agent Systems and Negotiation
- Topic Modeling
- Machine Learning and Algorithms
- AI-based Problem Solving and Planning
Papers in
-
- Logic, Reasoning, and Knowledge 11
- Multi-Agent Systems and Negotiation 8
- Topic Modeling 5
- Machine Learning and Algorithms 4
- Natural Language Processing Techniques 3
- Explainable Artificial Intelligence (XAI) 3
- Semantic Web and Ontologies 2
-
- Advanced Algebra and Logic 2
- Co-authors
- Alessandra Russo (15 shared papers)Krysia Broda (7 shared papers)Elisa Bertino (7 shared papers)Jorge Lobo (5 shared papers)Richard A. Abrams (1 shared paper)Geeth de Mel (2 shared papers)Irene Manotas (3 shared papers)Arosha K. Bandara (1 shared paper)
- Journals
- Artificial Intelligence (1 paper)Theory and Practice of Logic Programming (1 paper)Machine Learning (1 paper)Experimental Brain Research (1 paper)Spiral (Imperial College London) (3 papers)
- Partner nations
- United KingdomUnited StatesSpain
In The Last Decade
Mark Law
17 papers receiving 120 citations
Peers
Comparison fields: 5 of 36
- Artificial Intelligence 95
- Software 6
- Computer Science Applications 5
- Information Systems 17
- Computer Networks and Communications 14
Countries citing papers authored by Mark Law
This map shows the geographic impact of Mark Law'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 Law with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Law more than expected).
Fields of papers citing papers by Mark Law
This network shows the impact of papers produced by Mark Law. 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 Law. The network helps show where Mark Law may publish in the future.
Co-authors
The 25 scholars most cited alongside Mark Law, 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 | 2018 | 23 | |
| 2 | 2016 | 21 | |
| 3 | 2020 | 21 | |
| 4 | 2019 | 14 | |
| 5 | 2019 | 11 | |
| 6 | 2002 | 9 | |
| 7 | 2023 | 4 | |
| 8 | 2021 | 4 | |
| 9 | 2019 | 3 | |
| 10 | 2022 | 2 | |
| 11 | 2021 | 2 | |
| 12 | 2021 | 2 | |
| 13 | An Abductive-Inductive Algorithm for Probabilistic Inductive Logic Programming. | 2016 | 1 |
| 14 | Machine Comprehension of Text Using Combinatory Categorial Grammar and Answer Set Programs. | 2017 | 1 |
| 15 | 2019 | 1 | |
| 16 | 2022 | 1 | |
| 17 | 2019 | 1 | |
| 18 | 2023 | 0 | |
| 19 | 2019 | 0 |
About Mark Law
Mark Law is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Sociology and Political Science and Statistical and Nonlinear Physics, having authored 19 papers that have together received 121 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (11 papers), Multi-Agent Systems and Negotiation (8 papers), Topic Modeling (5 papers), Machine Learning and Algorithms (4 papers), Natural Language Processing Techniques (3 papers), Explainable Artificial Intelligence (XAI) (3 papers), Semantic Web and Ontologies (2 papers) and Advanced Algebra and Logic (2 papers). The work is most often cited by research in Artificial Intelligence (95 citations), Software (6 citations), Computer Science Applications (5 citations), Information Systems (17 citations) and Computer Networks and Communications (14 citations). Mark Law has collaborated with scholars based in United Kingdom, United States and Spain. Frequent co-authors include Alessandra Russo, Krysia Broda, Elisa Bertino, Jorge Lobo, Richard A. Abrams, Geeth de Mel, Irene Manotas, Arosha K. Bandara, Gül Çalıklı and Luke Dickens. Their work appears in journals such as Artificial Intelligence, Theory and Practice of Logic Programming, Machine Learning, Experimental Brain Research and Spiral (Imperial College London).
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.