Stephen G. Soderland
Impact in
- Artificial Intelligence top 0.1%
- Topic Modeling
- Natural Language Processing Techniques
- Semantic Web and Ontologies
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
- Information Systems top 0.2%
- Web Data Mining and Analysis
- Information Retrieval and Search Behavior
Papers in
-
- Natural Language Processing Techniques 41
- Topic Modeling 29
- Advanced Text Analysis Techniques 15
- Machine Learning in Healthcare 3
- Text and Document Classification Technologies 3
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- Web Data Mining and Analysis 15
- Co-authors
- Oren Etzioni (33 shared papers)Michael Cafarella (6 shared papers)Michele Banko (3 shared papers)Daniel S. Weld (16 shared papers)Anthony Fader (3 shared papers)Doug Downey (8 shared papers)Matt Broadhead (1 shared paper)Tal Shaked (4 shared papers)
- Journals
- Theory and applications of categories (3 papers)Artificial Intelligence (3 papers)Integrated Computer-Aided Engineering (1 paper)AI Magazine (1 paper)Transactions of the Association for Computational Linguistics (1 paper)
- Partner nations
- United StatesIsrael
In The Last Decade
Stephen G. Soderland
63 papers receiving 7k citations
Stephen G. Soderland's Hit Papers
Peers
Comparison fields: 5 of 120
- Artificial Intelligence 6k
- Information Systems 1.7k
- General Social Sciences 57
- Computer Science Applications 74
- Health Information Management 88
Countries citing papers authored by Stephen G. Soderland
This map shows the geographic impact of Stephen G. 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 G. 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 G. Soderland more than expected).
Fields of papers citing papers by Stephen G. Soderland
This network shows the impact of papers produced by Stephen G. 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 G. Soderland. The network helps show where Stephen G. Soderland may publish in the future.
Co-authors
The 25 scholars most cited alongside Stephen G. Soderland, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 65 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Open information extraction from the web Hit paper breakdown → | 2007 | 1016 |
| 2 | Identifying Relations for Open Information Extraction Hit paper breakdown → | 2011 | 860 |
| 3 | Unsupervised named-entity extraction from the Web: An experimental study Hit paper breakdown → | 2005 | 837 |
| 4 | Open information extraction from the web Hit paper breakdown → | 2008 | 752 |
| 5 | Learning Information Extraction Rules for Semi-Structured and Free Text Hit paper breakdown → | 1999 | 707 |
| 6 | Web-scale information extraction in knowitall Hit paper breakdown → | 2004 | 589 |
| 7 | Open Language Learning for Information Extraction Hit paper breakdown → | 2012 | 523 |
| 8 | Open information extraction: the second generation Hit paper breakdown → | 2011 | 340 |
| 9 | 2007 | 241 | |
| 10 | Learning to extract text-based information from the World Wide Web | 1997 | 150 |
| 11 | 2001 | 120 | |
| 12 | 2011 | 106 | |
| 13 | Towards Coherent Multi-Document Summarization | 2013 | 96 |
| 14 | 1992 | 92 | |
| 15 | 2013 | 88 | |
| 16 | Methods for domain-independent information extraction from the web: an experimental comparison | 2004 | 84 |
| 17 | 2005 | 82 | |
| 18 | What Is This, Anyway: Automatic Hypernym Discovery. | 2009 | 78 |
| 19 | 1995 | 65 | |
| 20 | 2008 | 54 |
About Stephen G. Soderland
Stephen G. Soderland is a scholar working on Artificial Intelligence, Information Systems, Health Information Management, Language and Linguistics and Molecular Biology, having authored 65 papers that have together received 7.7k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (41 papers), Topic Modeling (29 papers), Web Data Mining and Analysis (15 papers), Advanced Text Analysis Techniques (15 papers), Biomedical Text Mining and Ontologies (6 papers), Electronic Health Records Systems (3 papers), Machine Learning in Healthcare (3 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Artificial Intelligence (6k citations), Information Systems (1.7k citations), General Social Sciences (57 citations), Computer Science Applications (74 citations) and Health Information Management (88 citations). Stephen G. Soderland has collaborated with scholars based in United States and Israel. Frequent co-authors include Oren Etzioni, Michael Cafarella, Michele Banko, Daniel S. Weld, Anthony Fader, Doug Downey, Matt Broadhead, Tal Shaked, Ana-Maria Popescu and Janara Christensen. Their work appears in journals such as Theory and applications of categories, Artificial Intelligence, Integrated Computer-Aided Engineering, AI Magazine and Transactions of the Association for Computational Linguistics.
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.