Daniel G. Schwartz
- Artificial Intelligence top 5%
- Logic, Reasoning, and Knowledge 17
- Semantic Web and Ontologies 8
- Fuzzy Logic and Control Systems 6
- Multi-Agent Systems and Negotiation 4
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- Advanced Algebra and Logic 13
- Rough Sets and Fuzzy Logic 13
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- Multi-Criteria Decision Making 6
- Statistics and Probability top 10%
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- Network Security and Intrusion Detection 4
- Co-authors
- George J. KlirH. W. LewisMarek J. DrużdżelErcüment YılmazJohn DowlingHanna WasylukSadoon AziziAgnieszka Oniśko
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsManagement Science and Operations Research
- Journals
- Proceedings of the IEEE (1 paper)Information Sciences (2 papers)Artificial Intelligence (2 papers)
- Partner nations
- United StatesJapanIran
In The Last Decade
Daniel G. Schwartz
40 papers receiving 297 citations
Peers
Comparison fields: 5 of 60
- Artificial Intelligence 216
- Computational Theory and Mathematics 81
- Management Science and Operations Research 60
- Statistics and Probability 25
- Software 10
Countries citing papers authored by Daniel G. Schwartz
This map shows the geographic impact of Daniel G. Schwartz'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 Daniel G. Schwartz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel G. Schwartz more than expected).
Fields of papers citing papers by Daniel G. Schwartz
This network shows the impact of papers produced by Daniel G. Schwartz. 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 Daniel G. Schwartz. The network helps show where Daniel G. Schwartz may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Daniel G. Schwartz, 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 | 2022 | 10 | |
| 2 | 2021 | 5 | |
| 3 | 2020 | 9 | |
| 4 | 2018 | 1 | |
| 5 | 2015 | 1 | |
| 6 | Case-oriented alert correlation | 2008 | 1 |
| 7 | Application of case-based reasoning to multi-sensor network intrusion detection | 2005 | 0 |
| 8 | An XML Distance Measure. | 2005 | 6 |
| 9 | 2005 | 2 | |
| 10 | A MetaData Architecture for Case-Based Reasoning. | 2004 | 2 |
| 11 | 2004 | 1 | |
| 12 | 2003 | 6 | |
| 13 | 2003 | 0 | |
| 14 | 2003 | 0 | |
| 15 | 2003 | 0 | |
| 16 | Knowledge Engineering for Very Large Decision-analytic Medical Models | 1999 | 10 |
| 17 | 1995 | 6 | |
| 18 | 1992 | 55 | |
| 19 | 1991 | 13 | |
| 20 | Outline of a naive semantics for reasoning with qualitative linguistic information | 1989 | 8 |
About Daniel G. Schwartz
Daniel G. Schwartz is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research, having authored 44 papers that have together received 323 indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (17 papers), Advanced Algebra and Logic (13 papers), Rough Sets and Fuzzy Logic (13 papers), Semantic Web and Ontologies (8 papers), Multi-Criteria Decision Making (6 papers), Fuzzy Logic and Control Systems (6 papers), Multi-Agent Systems and Negotiation (4 papers) and Network Security and Intrusion Detection (4 papers). The work is most often cited by research in Artificial Intelligence (216 citations), Computational Theory and Mathematics (81 citations) and Management Science and Operations Research (60 citations). Daniel G. Schwartz has collaborated with scholars based in United States, Japan and Iran. Frequent co-authors include George J. Klir, H. W. Lewis, Marek J. Drużdżel, Ercüment Yılmaz, John Dowling, Hanna Wasyluk, Sadoon Azizi, Agnieszka Oniśko, Andreas Paepcke and Dan E. Tamir. Their work appears in journals such as Proceedings of the IEEE, Information Sciences and 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.