Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Unsupervised named-entity extraction from the Web: An experimental study
2005710 citationsOren Etzioni, Michael Cafarella et al.profile →
Open information extraction from the web
2008655 citationsOren Etzioni, Stephen Soderland et al.profile →
Web-scale information extraction in knowitall
2004498 citationsOren Etzioni, Michael Cafarella et al.profile →
Countries citing papers authored by Daniel S. Weld
Since
Specialization
Citations
This map shows the geographic impact of Daniel S. Weld's research. 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 Daniel S. Weld with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel S. Weld more than expected).
This network shows the impact of papers produced by Daniel S. Weld. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel S. Weld. The network helps show where Daniel S. Weld may publish in the future.
Co-authorship network of co-authors of Daniel S. Weld
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel S. Weld.
A scholar is included among the top collaborators of Daniel S. Weld based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Daniel S. Weld. Daniel S. Weld is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lo, Kyle, Lucy Lu Wang, Mark E Neumann, Rodney Kinney, & Daniel S. Weld. (2019). GORC: A large contextual citation graph of academic papers. arXiv (Cornell University).3 indexed citations
8.
Ferguson, James F., et al.. (2016). University of Washington TAC-KBP 2016 System Description.. Theory and applications of categories.2 indexed citations
9.
Soderland, Stephen, et al.. (2015). Combining Open IE and Distant Supervision for KBP Slot Filling.. Theory and applications of categories.2 indexed citations
10.
Soderland, Stephen, et al.. (2013). Open Information Extraction to KBP Relations in 3 Hours.. Theory and applications of categories.17 indexed citations
11.
Hoffmann, Raphael, Congle Zhang, & Daniel S. Weld. (2010). Learning 5000 Relational Extractors. Meeting of the Association for Computational Linguistics. 286–295.81 indexed citations
Weld, Daniel S., Fei Wu, Eytan Adar, et al.. (2008). Intelligence in wikipedia. National Conference on Artificial Intelligence. 1609–1614.42 indexed citations
14.
Etzioni, Oren, Michael Cafarella, Doug Downey, et al.. (2004). Methods for domain-independent information extraction from the web: an experimental comparison. National Conference on Artificial Intelligence. 391–398.73 indexed citations
15.
Soderland, Stephen, Oren Etzioni, Tal Shaked, & Daniel S. Weld. (2004). The use of web-based statistics to validate, information extraction. National Conference on Artificial Intelligence.12 indexed citations
16.
Anderson, Corin R., Pedro Domingos, & Daniel S. Weld. (2001). Adaptive web navigation for wireless devices. International Joint Conference on Artificial Intelligence. 879–884.66 indexed citations
17.
Ives, Zachary G., Alon Halevy, & Daniel S. Weld. (2001). Integrating Network-Bound XML Data. ScholarlyCommons (University of Pennsylvania). 24. 20–26.14 indexed citations
18.
Lau, Tessa, Pedro Domingos, & Daniel S. Weld. (2000). Version Space Algebra and its Application to Programming by Demonstration. International Conference on Machine Learning. 527–534.63 indexed citations
19.
Ives, Zachary G., Alon Y. Levy, Daniel S. Weld, Daniela Florescu, & Marc Friedman. (2000). Adaptive Query Processing for Internet Applications. ScholarlyCommons (University of Pennsylvania). 23. 19–26.31 indexed citations
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.