David B. Skalak
- Artificial Intelligence top 2%
- Political Science and International Relations top 2%
- Law top 2%
- Information Systems top 10%
- Economics and Econometrics
- Topics
- Multi-Agent Systems and Negotiation (10 papers)Artificial Intelligence in Law (7 papers)Data Mining Algorithms and Applications (5 papers)
- Journals
- Artificial Intelligence and LawInternational Journal of Man-Machine StudiesInternational Joint Conference on Artificial Intelligence
- Partner nations
- United States
In The Last Decade
David B. Skalak
20 papers receiving 538 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 514
- Political Science and International Relations 267
- Law 84
- Information Systems 66
- Economics and Econometrics 63
Countries citing papers authored by David B. Skalak
This map shows the geographic impact of David B. Skalak'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 David B. Skalak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David B. Skalak more than expected).
Fields of papers citing papers by David B. Skalak
This network shows the impact of papers produced by David B. Skalak. 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 David B. Skalak. The network helps show where David B. Skalak may publish in the future.
Co-authorship network of co-authors of David B. Skalak
This figure shows the co-authorship network connecting the top 25 collaborators of David B. Skalak. A scholar is included among the top collaborators of David B. Skalak 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 David B. Skalak. David B. Skalak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 9 | |
| 3 | 59 | |
| 4 | Prototype Selection for Composite Nearest Neighbor Classifiers TITLE2 | 1 |
| 5 | Prototype Selection for Composite Nearest Neighbor Classifiers | 45 |
| 6 | 1 | |
| 7 | Heuristic harvesting of information for case-based argument | 10 |
| 8 | Supporting Legal Arguments through Heuristic Retrieval | 10 |
| 9 | Case-based diagnostic analysis in a blackboard architecture | 26 |
| 10 | 10 | |
| 11 | 26 | |
| 12 | Using a Genetic Algorithm to Learn Prototypes for Case Retrieval and Classification | 13 |
| 13 | Diagnostic Case Retrieval Guided by Evaluation and Feedback | 2 |
| 14 | 113 | |
| 15 | 140 | |
| 16 | 22 | |
| 17 | Inductive learning in a mixed paradigm setting | 14 |
| 18 | 81 | |
| 19 | 29 | |
| 20 | 15 |
About David B. Skalak
David B. Skalak is a scholar working on Artificial Intelligence, Political Science and International Relations and Software, having authored 20 papers that have together received 629 indexed citations. Recurring topics across this work include Multi-Agent Systems and Negotiation (10 papers), Artificial Intelligence in Law (7 papers) and Data Mining Algorithms and Applications (5 papers). The work is most often cited by research in Artificial Intelligence (514 citations), Political Science and International Relations (267 citations) and Law (84 citations). David B. Skalak has collaborated with scholars based in United States. Frequent co-authors include Edwina L. Rissland, M. Friedman, E. L. Rissland and Ronald P. Loui. Their work appears in journals such as Artificial Intelligence and Law, International Journal of Man-Machine Studies and International Joint Conference on Artificial Intelligence.
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.