Domain-specific keyphrase extraction
Impact in
Classified as
- Journal
- Research Commons (University of Waikato)
In The Last Decade
doi.org/w5481877 →Countries where authors are citing Domain-specific keyphrase extraction
This map shows the geographic impact of Domain-specific keyphrase extraction. 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 Domain-specific keyphrase extraction with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Domain-specific keyphrase extraction more than expected).
Fields of papers citing Domain-specific keyphrase extraction
This network shows the impact of Domain-specific keyphrase extraction. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Domain-specific keyphrase extraction.
About Domain-specific keyphrase extraction
This paper, published in 1999, received 509 indexed citations . Written by Eibe Frank, Gordon W. Paynter, Ian H. Witten, Carl Gutwin and Craig G. Nevill-Manning covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (483 citations), Information Systems (215 citations), Molecular Biology (43 citations), Computer Vision and Pattern Recognition (18 citations) and Computer Networks and Communications (17 citations). Published in Research Commons (University of Waikato).
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/w5481877.