Lev Ratinov
Impact in
- Artificial Intelligence top 1%
- Topic Modeling
- Natural Language Processing Techniques
- Text and Document Classification Technologies
- Advanced Text Analysis Techniques
- Semantic Web and Ontologies
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- Data Quality and Management
Papers in
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- Topic Modeling 9
- Natural Language Processing Techniques 7
- Text and Document Classification Technologies 3
- Semantic Web and Ontologies 3
- Bayesian Modeling and Causal Inference 2
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- Advanced Database Systems and Queries 2
- Co-authors
- Dan Roth (7 shared papers)Ming‐Wei Chang (4 shared papers)Vivek Srikumar (2 shared papers)Rakesh Gupta (1 shared paper)Ehud Gudes (2 shared papers)
- Journals
- Machine Learning (1 paper)Meeting of the Association for Computational Linguistics (1 paper)Empirical Methods in Natural Language Processing (1 paper)Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) (1 paper)National Conference on Artificial Intelligence (3 papers)
- Partner nations
- United StatesIsraelJapan
In The Last Decade
Lev Ratinov
11 papers receiving 1.3k citations
Lev Ratinov's Hit Papers
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 1.3k
- Management Science and Operations Research 153
- Information Systems 183
- Computer Vision and Pattern Recognition 133
- Communication 36
Countries citing papers authored by Lev Ratinov
This map shows the geographic impact of Lev Ratinov'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 Lev Ratinov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lev Ratinov more than expected).
Fields of papers citing papers by Lev Ratinov
This network shows the impact of papers produced by Lev Ratinov. 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 Lev Ratinov. The network helps show where Lev Ratinov may publish in the future.
Co-authors
The 5 scholars most cited alongside Lev Ratinov, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Design challenges and misconceptions in named entity recognition Hit paper breakdown → | 2009 | 916 |
| 2 | Importance of semantic representation: dataless classification | 2008 | 148 |
| 3 | Guiding Semi-Supervision with Constraint-Driven Learning | 2007 | 121 |
| 4 | 2012 | 74 | |
| 5 | Learning and inference with constraints | 2008 | 47 |
| 6 | Learning-based Multi-Sieve Co-reference Resolution with Knowledge | 2012 | 31 |
| 7 | Text categorization with knowledge transfer from heterogeneous data sources | 2008 | 30 |
| 8 | 2004 | 9 | |
| 9 | Conceptual Search And Text Categorization | 2008 | 5 |
| 10 | 2005 | 4 | |
| 11 | 2024 | 2 |
About Lev Ratinov
Lev Ratinov is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Molecular Biology and Management Science and Operations Research, having authored 11 papers that have together received 1.4k indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (7 papers), Text and Document Classification Technologies (3 papers), Semantic Web and Ontologies (3 papers), Advanced Database Systems and Queries (2 papers), Bayesian Modeling and Causal Inference (2 papers), Service-Oriented Architecture and Web Services (2 papers) and Data Quality and Management (1 paper). The work is most often cited by research in Artificial Intelligence (1.3k citations), Management Science and Operations Research (153 citations), Information Systems (183 citations), Computer Vision and Pattern Recognition (133 citations) and Communication (36 citations). Lev Ratinov has collaborated with scholars based in United States, Israel and Japan. Frequent co-authors include Dan Roth, Ming‐Wei Chang, Vivek Srikumar, Rakesh Gupta and Ehud Gudes. Their work appears in journals such as Machine Learning, Meeting of the Association for Computational Linguistics, Empirical Methods in Natural Language Processing, Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign) and National Conference on Artificial Intelligence.
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.