A Maximum-Entropy-Inspired Parser
Impact in
Classified as
- Authors
- Eugene Charniak
- Journal
- The COCOON platform (University of Paris)
In The Last Decade
doi.org/w3385343 →Countries where authors are citing A Maximum-Entropy-Inspired Parser
This map shows the geographic impact of A Maximum-Entropy-Inspired Parser. 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 A Maximum-Entropy-Inspired Parser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A Maximum-Entropy-Inspired Parser more than expected).
Fields of papers citing A Maximum-Entropy-Inspired Parser
This network shows the impact of A Maximum-Entropy-Inspired Parser. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the A Maximum-Entropy-Inspired Parser.
About A Maximum-Entropy-Inspired Parser
This paper, published in 1999, received 1.0k indexed citations . Written by Eugene Charniak covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (999 citations), Molecular Biology (82 citations), Information Systems (60 citations), Computer Vision and Pattern Recognition (51 citations) and Developmental and Educational Psychology (22 citations). Published in The COCOON platform (University of Paris).
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This paper is also available at doi.org/w3385343.