Fast algorithms for mining association rules
- Journal
- Very Large Data Bases
In The Last Decade
doi.org/w8877663 →Countries where authors are citing Fast algorithms for mining association rules
This map shows the geographic impact of Fast algorithms for mining 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 Fast algorithms for mining 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 Fast algorithms for mining association rules more than expected).
Fields of papers citing Fast algorithms for mining association rules
This network shows the impact of Fast algorithms for mining 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 Fast algorithms for mining association rules.
About Fast algorithms for mining association rules
This paper, published in 1998, received 6.6k indexed citations . Written by Rakesh Agrawal and Ramakrishnan Srikant covering the research area of Artificial Intelligence, Computational Theory and Mathematics and Information Systems. It is primarily cited by scholars working on Information Systems (4.8k citations), Artificial Intelligence (3.1k citations) and Computational Theory and Mathematics (2.6k 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/w8877663.