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.
Countries citing papers authored by Stephen Soderland
Since
Specialization
Citations
This map shows the geographic impact of Stephen Soderland'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 Stephen Soderland with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen Soderland more than expected).
Fields of papers citing papers by Stephen Soderland
This network shows the impact of papers produced by Stephen Soderland. 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 Stephen Soderland. The network helps show where Stephen Soderland may publish in the future.
Co-authorship network of co-authors of Stephen Soderland
This figure shows the co-authorship network connecting the top 25 collaborators of Stephen Soderland.
A scholar is included among the top collaborators of Stephen Soderland 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 Stephen Soderland. Stephen Soderland is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Ferguson, James F., et al.. (2016). University of Washington TAC-KBP 2016 System Description.. Theory and applications of categories.2 indexed citations
2.
Soderland, Stephen, et al.. (2015). Combining Open IE and Distant Supervision for KBP Slot Filling.. Theory and applications of categories.2 indexed citations
3.
Soderland, Stephen, et al.. (2013). Open Information Extraction to KBP Relations in 3 Hours.. Theory and applications of categories.17 indexed citations
4.
Christensen, Janara, Stephen Soderland, & Oren Etzioni. (2013). Towards Coherent Multi-Document Summarization. North American Chapter of the Association for Computational Linguistics. 1163–1173.78 indexed citations
5.
Balasubramanian, Niranjan, Stephen Soderland, & Oren Etzioni. (2012). Rel-grams: A Probabilistic Model of Relations in Text. North American Chapter of the Association for Computational Linguistics. 101–105.8 indexed citations
Etzioni, Oren, Anthony Fader, Janara Christensen, Stephen Soderland, & Mausam Mausam. (2011). Open information extraction: the second generation. International Joint Conference on Artificial Intelligence. 3–10.274 indexed citations
8.
Christensen, Janara, Stephen Soderland, & Oren Etzioni. (2010). Semantic Role Labeling for Open Information Extraction. North American Chapter of the Association for Computational Linguistics. 52–60.50 indexed citations
9.
Poon, Hoifung, Janara Christensen, Pedro Domingos, et al.. (2010). Machine Reading at the University of Washington. North American Chapter of the Association for Computational Linguistics. 87–95.22 indexed citations
10.
Fader, Anthony, Stephen Soderland, & Oren Etzioni. (2010). Extracting Sequences from the Web. Meeting of the Association for Computational Linguistics. 286–290.1 indexed citations
11.
Ritter, Alan, Stephen Soderland, & Oren Etzioni. (2009). What Is This, Anyway: Automatic Hypernym Discovery.. National Conference on Artificial Intelligence. 88–93.70 indexed citations
Soderland, Stephen & Bhushan Mandhani. (2007). Moving from Textual Relations to Ontologized Relations.. National Conference on Artificial Intelligence. 85–90.14 indexed citations
14.
Soderland, Stephen, et al.. (2006). Ambiguity Reduction for Machine Translation: Human-Computer Collaboration.. Conference of the Association for Machine Translation in the Americas. 193–202.2 indexed citations
15.
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
16.
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
17.
Downey, Doug, Oren Etzioni, Stephen Soderland, & Daniel S. Weld. (2004). Learning text patterns for web information extraction and assessment. National Conference on Artificial Intelligence. 50–55.26 indexed citations
18.
Downey, Doug, et al.. (2004). Learning Text Patterns for Web Information Extraction and Assessment (Extended Version).2 indexed citations
19.
Fuller, Sherrilynne S., et al.. (2002). Modeling a Concept-based Information System to Promote Scientific Discovery: The Telemakus System.. Europe PMC (PubMed Central). 1023–1023.4 indexed citations
20.
Soderland, Stephen. (1997). Learning to extract text-based information from the World Wide Web. Knowledge Discovery and Data Mining. 251–254.126 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.