UCI Repository of Machine Learning Databases
- Authors
- Christopher J. Merz
- Journal
- Medical Entomology and Zoology
In The Last Decade
doi.org/w29070807 →Countries where authors are citing UCI Repository of Machine Learning Databases
This map shows the geographic impact of UCI Repository of Machine Learning Databases. 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 UCI Repository of Machine Learning Databases with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites UCI Repository of Machine Learning Databases more than expected).
Fields of papers citing UCI Repository of Machine Learning Databases
This network shows the impact of UCI Repository of Machine Learning Databases. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the UCI Repository of Machine Learning Databases.
About UCI Repository of Machine Learning Databases
This paper, published in 1996, received 1.6k indexed citations . Written by Christopher J. Merz covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (1.4k citations), Computer Vision and Pattern Recognition (431 citations) and Information Systems (413 citations). Published in Medical Entomology and Zoology.
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/w29070807.