Sampling Large Databases for Association Rules
Impact in
Classified as
- Authors
- Hannu Toivonen
- Journal
- Very Large Data Bases
In The Last Decade
doi.org/w407810 →Countries where authors are citing Sampling Large Databases for Association Rules
This map shows the geographic impact of Sampling Large Databases for Association Rules. 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 Sampling Large Databases for Association Rules with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sampling Large Databases for Association Rules more than expected).
Fields of papers citing Sampling Large Databases for Association Rules
This network shows the impact of Sampling Large Databases for Association Rules. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Sampling Large Databases for Association Rules.
About Sampling Large Databases for Association Rules
This paper, published in 1996, received 690 indexed citations . Written by Hannu Toivonen covering the research area of Computational Theory and Mathematics, Artificial Intelligence and Information Systems. It is primarily cited by scholars working on Information Systems (595 citations), Computational Theory and Mathematics (430 citations), Artificial Intelligence (359 citations), Signal Processing (279 citations) and Computer Networks and Communications (96 citations). Published in Very Large Data Bases.
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/w407810.