This map shows the geographic impact of Eugene Santos'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 Eugene Santos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eugene Santos more than expected).
This network shows the impact of papers produced by Eugene Santos. 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 Eugene Santos. The network helps show where Eugene Santos may publish in the future.
Co-authorship network of co-authors of Eugene Santos
This figure shows the co-authorship network connecting the top 25 collaborators of Eugene Santos.
A scholar is included among the top collaborators of Eugene Santos 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 Eugene Santos. Eugene Santos is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Yu, F. Richard & Eugene Santos. (2016). On Modeling the Interplay Between Opinion Change and Formation.. The Florida AI Research Society. 140–145.5 indexed citations
3.
Nijholt, Anton, Ronald C. Arkin, Sébastien Brault, et al.. (2012). Computational Deception and Noncooperation. IEEE Intelligent Systems. 27(6). 60–75.4 indexed citations
4.
Santos, Eugene, et al.. (2011). Tuning a Bayesian Knowledge Base. The Florida AI Research Society.4 indexed citations
5.
Santos, Eugene, John Wilkinson, & Eunice E. Santos. (2009). Bayesian Knowledge Fusion. The Florida AI Research Society. 559–564.18 indexed citations
6.
Santos, Eunice E., et al.. (2008). Culturally infused social network Analysis. International Conference on Artificial Intelligence. 449–455.9 indexed citations
7.
Nguyen, Hien & Eugene Santos. (2007). An Evaluation of the Accuracy of Capturing User Intent for Information Retrieval.. International Conference on Artificial Intelligence. 341–350.2 indexed citations
8.
Santos, Eunice E., et al.. (2006). A Framework for Complex Adaptive Systems.. Parallel and Distributed Processing Techniques and Applications. 437–443.1 indexed citations
Lee, Jung Jin, Robert McCartney, & Eugene Santos. (2001). Learning and Predicting User Behavior for Particular Resource Use. 84(10). 177–181.1 indexed citations
13.
Johnson, Gregory & Eugene Santos. (2000). Generalizing Knowledge Representation Rules for Acquiring and Validating Uncertain Knowledge. The Florida AI Research Society. 186–190.6 indexed citations
14.
Santos, Eunice E. & Eugene Santos. (2000). Cache Diversity in Genetic Algorithm Design. The Florida AI Research Society. 107–111.1 indexed citations
15.
Santos, Eugene, et al.. (1999). Identifying and Handling Structural Incompleteness for Validation of Probabilistic Knowledge-Bases. The Florida AI Research Society. 506–510.5 indexed citations
16.
Santos, Eugene, et al.. (1999). Solving Hard Computational Problems through Collections (Portfolios) of Cooperative Heterogeneous Algorithms. The Florida AI Research Society. 356–360.3 indexed citations
17.
Santos, Eugene, et al.. (1999). Dynamic User Model Construction with Bayesian Networks for Intelligent Information Queries. The Florida AI Research Society. 3–7.9 indexed citations
18.
Santos, Eugene, et al.. (1998). Intelligent Interface Agents for Intelligent Environments.2 indexed citations
Charniak, Eugene & Eugene Santos. (1992). Dynamic MAP calculations for abduction. National Conference on Artificial Intelligence. 552–557.12 indexed citations
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.