Clustering by means of medoids
- Authors
- L. KaufmanPeter J. Rousseeuw
- Journal
- Lirias (KU Leuven)
In The Last Decade
doi.org/w34577298 →Countries where authors are citing Clustering by means of medoids
This map shows the geographic impact of Clustering by means of medoids. 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 Clustering by means of medoids with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Clustering by means of medoids more than expected).
Fields of papers citing Clustering by means of medoids
This network shows the impact of Clustering by means of medoids. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Clustering by means of medoids.
About Clustering by means of medoids
This paper, published in 1987, received 801 indexed citations . Written by L. Kaufman and Peter J. Rousseeuw. It is primarily cited by scholars working on Artificial Intelligence (377 citations), Computer Vision and Pattern Recognition (174 citations) and Signal Processing (153 citations). Published in Lirias (KU Leuven).
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/w34577298.