Countries citing papers authored by John D. Lowrance
Since
Specialization
Citations
This map shows the geographic impact of John D. Lowrance'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 John D. Lowrance with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John D. Lowrance more than expected).
Fields of papers citing papers by John D. Lowrance
This network shows the impact of papers produced by John D. Lowrance. 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 John D. Lowrance. The network helps show where John D. Lowrance may publish in the future.
Co-authorship network of co-authors of John D. Lowrance
This figure shows the co-authorship network connecting the top 25 collaborators of John D. Lowrance.
A scholar is included among the top collaborators of John D. Lowrance 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 John D. Lowrance. John D. Lowrance is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lowrance, John D., et al.. (2005). Fostering Collaboration with a Semantic Index over Textual Contributions.. National Conference on Artificial Intelligence. 99–106.1 indexed citations
Wolverton, Michael, et al.. (2003). LAW: A Workbench for Approximate Pattern Matching in Relational Data. Innovative Applications of Artificial Intelligence. 143–150.15 indexed citations
Paley, Suzanne, John D. Lowrance, & Peter D. Karp. (1997). A generic knowledge-base browser and editor. National Conference on Artificial Intelligence. 1045–1051.20 indexed citations
12.
Saffiotti, Alessandro, et al.. (1993). A fuzzy controller for flakey, the robot. National Conference on Artificial Intelligence. 864–864.
13.
Ruspini, Enrique H., John D. Lowrance, & Thomas M. Strat. (1992). Understanding evidential reasoning. International Journal of Approximate Reasoning. 6(3). 401–424.24 indexed citations
14.
Strat, Thomas M. & John D. Lowrance. (1989). Explaining evidential analyses. International Journal of Approximate Reasoning. 3(4). 299–353.16 indexed citations
15.
Lowrance, John D., Thomas D. Garvey, & Thomas M. Strat. (1986). A framework for evidential-reasoning systems.12 indexed citations
16.
Lowrance, John D., et al.. (1984). Reasoning About Control: An Evidential Approach. Defense Technical Information Center (DTIC).5 indexed citations
17.
Lowrance, John D. & Thomas D. Garvey. (1982). Evidential reasoning: a developing concept. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).27 indexed citations
18.
Lowrance, John D.. (1982). Dependency-graph models of evidential support. Medical Entomology and Zoology.16 indexed citations
19.
Garvey, Thomas D., John D. Lowrance, & Martin A. Fischler. (1981). An inference technique for integrating knowledge from disparate sources. International Joint Conference on Artificial Intelligence. 309–325.143 indexed citations
20.
Williams, Thomas D., John D. Lowrance, Allen R. Hanson, & Edward M. Riseman. (1977). Model-building in the visions system. International Joint Conference on Artificial Intelligence. 644–645.6 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.