Advances in the Dempster-Shafer theory of evidence
- Journal
- Institutional Research Information System (Università degli Studi di Trento)
In The Last Decade
doi.org/w7453855 →Countries where authors are citing Advances in the Dempster-Shafer theory of evidence
This map shows the geographic impact of Advances in the Dempster-Shafer theory of evidence. 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 Advances in the Dempster-Shafer theory of evidence with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Advances in the Dempster-Shafer theory of evidence more than expected).
Fields of papers citing Advances in the Dempster-Shafer theory of evidence
This network shows the impact of Advances in the Dempster-Shafer theory of evidence. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Advances in the Dempster-Shafer theory of evidence.
About Advances in the Dempster-Shafer theory of evidence
This paper, published in 1994, received 588 indexed citations . Written by Ronald R. Yager, Janusz Kacprzyk and Mario Fedrizzi covering the research area of Management Information Systems. It is primarily cited by scholars working on Artificial Intelligence (302 citations), Computational Theory and Mathematics (208 citations) and Management Science and Operations Research (202 citations). Published in Institutional Research Information System (Università degli Studi di Trento).
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.
This paper is also available at doi.org/w7453855.