Joel Nothman

13.1k total citations
30 papers, 969 citations indexed

About

Joel Nothman is a scholar working on Artificial Intelligence, Management Science and Operations Research and Communication. According to data from OpenAlex, Joel Nothman has authored 30 papers receiving a total of 969 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 9 papers in Management Science and Operations Research and 5 papers in Communication. Recurrent topics in Joel Nothman's work include Natural Language Processing Techniques (26 papers), Topic Modeling (24 papers) and Data Quality and Management (9 papers). Joel Nothman is often cited by papers focused on Natural Language Processing Techniques (26 papers), Topic Modeling (24 papers) and Data Quality and Management (9 papers). Joel Nothman collaborates with scholars based in Australia, United States and China. Joel Nothman's co-authors include James Curran, Tara Murphy, Will Radford, Ben Hachey, Nicky Ringland, Heng Ji, Matthew Honnibal, Boliang Zhang, Xiaoman Pan and Kevin Knight and has published in prestigious journals such as Artificial Intelligence, JMIR mhealth and uhealth and Theory and applications of categories.

In The Last Decade

Joel Nothman

30 papers receiving 852 citations

Peers

Joel Nothman

AI

MSOR

IS

CVPR

COMMU

Andrés García-Silva Spain

Lev Ratinov United States

Ugo Scaiella Italy

Andras Csomai United States

Radu Florian United States

Víctor Fresno Spain

Rafael Muñoz Spain

Jun’ichi Kazama Japan

Alan Akbik Germany

Jakub Piskorski Italy

Andrés García-Silva Spain

Joel Nothman

586 ×0.7

AI

115 ×0.7

MSOR

224 ×1.8

IS

47 ×0.5

CVPR

42 ×0.5

COMMU

Citations per year, relative to Joel Nothman Joel Nothman (= 1×) peers Andrés García-Silva

Countries citing papers authored by Joel Nothman

Since Specialization

Citations

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

Fields of papers citing papers by Joel Nothman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joel Nothman

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

All Works

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20 of 20 papers shown

1.

Klimis, Harry, Joel Nothman, N. Wah Cheung, et al.. (2021). Text Message Analysis Using Machine Learning to Assess Predictors of Engagement With Mobile Health Chronic Disease Prevention Programs: Content Analysis. JMIR mhealth and uhealth. 9(11). e27779–e27779. 6 indexed citations

2.

Ji, Heng, Avirup Sil, Hoa Trang Dang, Ian Soboroff, & Joel Nothman. (2019). Overview of TAC-KBP 2019 Fine-grained Entity Extraction.. Theory and applications of categories. 2 indexed citations

3.

Nothman, Joel, et al.. (2018). Stop Word Lists in Free Open-source Software Packages. 29 indexed citations

4.

Pan, Xiaoman, Boliang Zhang, Jonathan May, et al.. (2017). Cross-lingual Name Tagging and Linking for 282 Languages. 1946–1958. 202 indexed citations

5.

Ji, Heng, Xiaoman Pan, Boliang Zhang, et al.. (2017). Overview of TAC-KBP2017 13 Languages Entity Discovery and Linking.. Theory and applications of categories. 21 indexed citations

6.

Nothman, Joel, et al.. (2017). English Event Detection With Translated Language Features. 293–298. 8 indexed citations

7.

Ji, Heng & Joel Nothman. (2016). Overview of TAC-KBP2016 Tri-lingual EDL and Its Impact on End-to-End KBP.. Theory and applications of categories. 10 indexed citations

8.

Ji, Heng, Joel Nothman, Ben Hachey, & Radu Florian. (2015). Overview of TAC-KBP2015 Tri-lingual Entity Discovery and Linking.. Theory and applications of categories. 55 indexed citations

9.

Radford, Will, Daniel Tse, Joel Nothman, et al.. (2015). The Computable News project. 903–908. 3 indexed citations

10.

Nothman, Joel, et al.. (2014). Unsupervised Biographical Event Extraction Using Wikipedia Traffic. 41–49. 2 indexed citations

11.

Nothman, Joel, et al.. (2014). Trading accuracy for faster named entity linking. 32–40. 1 indexed citations

12.

Nothman, Joel, et al.. (2014). Analysing recall loss in named entity slot filling. 820–830. 4 indexed citations

13.

Radford, Will, et al.. (2013). SYDNEY CMCRC at TAC 2013.. Theory and applications of categories. 4 indexed citations

14.

Nothman, Joel, Matthew Honnibal, Ben Hachey, & James Curran. (2012). Event Linking: Grounding Event Reference in a News Archive. Meeting of the Association for Computational Linguistics. 228–232. 17 indexed citations

15.

Radford, Will, et al.. (2012). (Almost) Total Recall - SYDNEY CMCRC at TAC 2012.. Theory and applications of categories. 8 indexed citations

16.

Hachey, Ben, Will Radford, Joel Nothman, Matthew Honnibal, & James Curran. (2012). Evaluating Entity Linking with Wikipedia. Artificial Intelligence. 194. 130–150. 155 indexed citations

17.

Nothman, Joel, Nicky Ringland, Will Radford, Tara Murphy, & James Curran. (2012). Learning multilingual named entity recognition from Wikipedia. Artificial Intelligence. 194. 151–175. 207 indexed citations

18.

Honnibal, Matthew, Joel Nothman, & James Curran. (2009). Evaluating a statistical CCG parser on Wikipedia. 38–41. 9 indexed citations

19.

Nothman, Joel, James Curran, & Tara Murphy. (2008). Transforming Wikipedia into Named Entity Training Data. 124–132. 57 indexed citations

20.

Nothman, Joel. (2008). Learning Named Entity Recognition from Wikipedia. 8 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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