Rik van Noord

498 total citations
13 papers, 142 citations indexed

About

Rik van Noord is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Rik van Noord has authored 13 papers receiving a total of 142 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Molecular Biology. Recurrent topics in Rik van Noord's work include Natural Language Processing Techniques (13 papers), Topic Modeling (11 papers) and Text Readability and Simplification (4 papers). Rik van Noord is often cited by papers focused on Natural Language Processing Techniques (13 papers), Topic Modeling (11 papers) and Text Readability and Simplification (4 papers). Rik van Noord collaborates with scholars based in Netherlands and Czechia. Rik van Noord's co-authors include Johan Bos, Antonio Toral, Lasha Abzianidze, Gertjan van Noord, Chunliu Wang, Rob van der Goot, Arianna Bisazza and Jennifer Spenader and has published in prestigious journals such as Language Resources and Evaluation, Transactions of the Association for Computational Linguistics and University of Groningen research database (University of Groningen / Centre for Information Technology).

In The Last Decade

Rik van Noord

13 papers receiving 138 citations

Peers

Countries citing papers authored by Rik van Noord

Since Specialization

Citations

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

Fields of papers citing papers by Rik van Noord

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rik van Noord. 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 Rik van Noord. The network helps show where Rik van Noord may publish in the future.

Co-authorship network of co-authors of Rik van Noord

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

All Works

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13 of 13 papers shown

#	Work	Indexed citations
1	Input Representations for Parsing Discourse Representation Structures: Comparing English with Chinese 2021 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Chunliu Wang, Rik van Noord, Arianna Bisazza, Johan Bos	4
2	Evaluating Text Generation from Discourse Representation Structures 2021 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Chunliu Wang, Rik van Noord, Arianna Bisazza, Johan Bos	4
3	Character-level Representations Improve DRS-based Semantic Parsing Even in the Age of BERT 2020 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Rik van Noord, Antonio Toral, Johan Bos	11
4	Neural Boxer at the IWCS Shared Task on DRS Parsing 2019 ·Data Archiving and Networked Services (DANS) ·Rik van Noord	4
5	Linguistic Information in Neural Semantic Parsing with Multiple Encoders 2019 ·Rik van Noord, Antonio Toral, Johan Bos	11
6	A Taxonomy for In-depth Evaluation of Normalization for User Generated Content 2018 ·Language Resources and Evaluation ·Rob van der Goot, Rik van Noord, Gertjan van Noord	7
7	Using Translated Data to Improve Deep Learning Author Profiling Models 2018 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·(unknown), (unknown), (unknown), Rik van Noord	4
8	Evaluating Scoped Meaning Representations 2018 ·Language Resources and Evaluation ·Rik van Noord, Lasha Abzianidze, (unknown), Johan Bos	19
9	Exploring Neural Methods for Parsing Discourse Representation Structures 2018 ·Transactions of the Association for Computational Linguistics ·Rik van Noord, Lasha Abzianidze, Antonio Toral, Johan Bos	29
10	Neural Semantic Parsing by Character-based Translation: Experiments with Abstract Meaning Representations 2017 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Rik van Noord, Johan Bos	36
11	The Meaning Factory at SemEval-2017 Task 9: Producing AMRs with Neural Semantic Parsing 2017 ·Rik van Noord, Johan Bos	2
12	Dealing with Co-reference in Neural Semantic Parsing 2017 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Rik van Noord, Johan Bos	9
13	Modeling the learning of the English past tense with memory-based learning 2015 ·University of Groningen research database (University of Groningen / Centre for Information Technology) ·Rik van Noord, Jennifer Spenader	2

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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