Yuval Krymolowski

493 total citations
15 papers, 284 citations indexed

About

Yuval Krymolowski is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Yuval Krymolowski has authored 15 papers receiving a total of 284 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 3 papers in Molecular Biology and 1 paper in Computer Vision and Pattern Recognition. Recurrent topics in Yuval Krymolowski's work include Natural Language Processing Techniques (12 papers), Topic Modeling (11 papers) and Machine Learning and Algorithms (4 papers). Yuval Krymolowski is often cited by papers focused on Natural Language Processing Techniques (12 papers), Topic Modeling (11 papers) and Machine Learning and Algorithms (4 papers). Yuval Krymolowski collaborates with scholars based in Israel, United Kingdom and Japan. Yuval Krymolowski's co-authors include Anna Korhonen, Ido Dagan, Shlomo Argamon, Ted Briscoe, Nigel Collier, Dan Roth, Vasin Punyakanok, Rob Koeling, Hervé Déjean and Erik F. Tjong Kim Sang and has published in prestigious journals such as Language Resources and Evaluation, Journal of Experimental & Theoretical Artificial Intelligence and Data Archiving and Networked Services (DANS).

In The Last Decade

Yuval Krymolowski

15 papers receiving 234 citations

Peers

Yuval Krymolowski

AI

MB

LL

DEP

IS

Keith Suderman United States

Harald Trost Austria

Vladislav Kuboň Czechia

Csaba Oravecz Hungary

Wolfgang Lezius Germany

Sandra Williams United Kingdom

Wojciech Skut Germany

Guido Minnen Germany

Choh Man Teng United States

Joakim Nivre United States

Keith Suderman United States

Yuval Krymolowski

244 ×0.9

AI

33 ×1.1

MB

39 ×2.6

LL

13 ×1.0

DEP

32 ×2.7

IS

Citations per year, relative to Yuval Krymolowski Yuval Krymolowski (= 1×) peers Keith Suderman

Countries citing papers authored by Yuval Krymolowski

Since Specialization

Citations

This map shows the geographic impact of Yuval Krymolowski'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 Yuval Krymolowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuval Krymolowski more than expected).

Fields of papers citing papers by Yuval Krymolowski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yuval Krymolowski. 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 Yuval Krymolowski. The network helps show where Yuval Krymolowski may publish in the future.

Co-authorship network of co-authors of Yuval Krymolowski

This figure shows the co-authorship network connecting the top 25 collaborators of Yuval Krymolowski. A scholar is included among the top collaborators of Yuval Krymolowski 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 Yuval Krymolowski. Yuval Krymolowski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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15 of 15 papers shown

1.

Sun, Lin, Anna Korhonen, & Yuval Krymolowski. (2008). Automatic Classification of English Verbs Using Rich Syntactic Features. International Joint Conference on Natural Language Processing. 769–774. 6 indexed citations

2.

Krymolowski, Yuval, et al.. (2008). Automatic Annotation of Morpho-Syntactic Dependencies in a Modern Hebrew Treebank. Data Archiving and Networked Services (DANS). 12. 77–90. 9 indexed citations

3.

Korhonen, Anna, Yuval Krymolowski, & Nigel Collier. (2008). The choice of features for classification of verbs in biomedical texts. 1. 449–456. 13 indexed citations

4.

Korhonen, Anna, Yuval Krymolowski, & Ted Briscoe. (2006). A Large Subcategorization Lexicon for Natural Language Processing Applications.. Language Resources and Evaluation. 1015–1020. 54 indexed citations

5.

Korhonen, Anna, Yuval Krymolowski, & Nigel Collier. (2006). Automatic classification of verbs in biomedical texts. 345–352. 17 indexed citations

6.

Krymolowski, Yuval, Beatrice Alex, & Jochen L. Leidner. (2004). BioCreative Task 2.1. The Edinburgh-Stanford System. 3 indexed citations

7.

Korhonen, Anna, et al.. (2003). Clustering polysemic subcategorization frame distributions semantically. 1. 64–71. 55 indexed citations

8.

Krymolowski, Yuval. (2002). Distinguishing easy and hard instances. 20. 1–6. 3 indexed citations

9.

Korhonen, Anna & Yuval Krymolowski. (2002). On the robustness of entropy-based similarity measures in evaluation of subcategorization acquisition systems. 20. 1–7. 11 indexed citations

10.

Krymolowski, Yuval & Ido Dagan. (2000). Incorporating compositional evidence in memory-based partial parsing. 53–60. 2 indexed citations

11.

Sang, Erik F. Tjong Kim, Walter Daelemans, Hervé Déjean, et al.. (2000). Applying system combination to base noun phrase identification. 2. 857–857. 25 indexed citations

12.

Dagan, Ido, et al.. (1999). A memory-based approach to learning shallow natural language patterns. Journal of Experimental & Theoretical Artificial Intelligence. 11(3). 369–390. 22 indexed citations

13.

Krymolowski, Yuval & Dan Roth. (1998). Incorporating Knowledge in Natural Language Learning: A Case Study. International Conference on Computational Linguistics. 8 indexed citations

14.

Argamon, Shlomo, Ido Dagan, & Yuval Krymolowski. (1998). A memory-based approach to learning shallow natural language patterns. Touro Scholar (Touro College). 1. 67–67. 52 indexed citations

15.

Argamon, Shlomo, Ido Dagan, & Yuval Krymolowski. (1998). A memory-based approach to learning shallow natural language patterns. 1. 67–67. 4 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.

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