Relation Extraction with Matrix Factorization and Universal Schemas
Impact in
Classified as
- Journal
- ScholarWorks@UMassAmherst (University of Massachusetts Amherst)
In The Last Decade
doi.org/w5480658 →Countries where authors are citing Relation Extraction with Matrix Factorization and Universal Schemas
This map shows the geographic impact of Relation Extraction with Matrix Factorization and Universal Schemas. 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 Relation Extraction with Matrix Factorization and Universal Schemas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Relation Extraction with Matrix Factorization and Universal Schemas more than expected).
Fields of papers citing Relation Extraction with Matrix Factorization and Universal Schemas
This network shows the impact of Relation Extraction with Matrix Factorization and Universal Schemas. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Relation Extraction with Matrix Factorization and Universal Schemas.
About Relation Extraction with Matrix Factorization and Universal Schemas
This paper, published in 2013, received 314 indexed citations . Written by Sebastian Riedel, Limin Yao, Andrew McCallum and Benjamin M. Marlin covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Artificial Intelligence (307 citations), Management Science and Operations Research (49 citations), Information Systems (35 citations), Molecular Biology (28 citations) and Computer Vision and Pattern Recognition (23 citations). Published in ScholarWorks@UMassAmherst (University of Massachusetts Amherst).
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/w5480658.