Scalable semantic web data management using vertical partitioning
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doi.org/w39673675 →Countries where authors are citing Scalable semantic web data management using vertical partitioning
This map shows the geographic impact of Scalable semantic web data management using vertical partitioning. 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 Scalable semantic web data management using vertical partitioning with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Scalable semantic web data management using vertical partitioning more than expected).
Fields of papers citing Scalable semantic web data management using vertical partitioning
This network shows the impact of Scalable semantic web data management using vertical partitioning. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Scalable semantic web data management using vertical partitioning.
About Scalable semantic web data management using vertical partitioning
This paper, published in 2007, received 357 indexed citations . Written by Daniel J. Abadi, Adam Marcus and Samuel Madden covering the research area of Information Systems, Artificial Intelligence and Computer Networks and Communications. It is primarily cited by scholars working on Artificial Intelligence (287 citations), Computer Networks and Communications (264 citations), Signal Processing (114 citations), Information Systems (104 citations) and Computer Vision and Pattern Recognition (96 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.
This paper is also available at doi.org/w39673675.