Richard Moot

572 total citations
16 papers, 60 citations indexed

About

Richard Moot is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Richard Moot has authored 16 papers receiving a total of 60 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 4 papers in Computational Theory and Mathematics and 1 paper in Information Systems. Recurrent topics in Richard Moot's work include Natural Language Processing Techniques (10 papers), Logic, programming, and type systems (6 papers) and Logic, Reasoning, and Knowledge (5 papers). Richard Moot is often cited by papers focused on Natural Language Processing Techniques (10 papers), Logic, programming, and type systems (6 papers) and Logic, Reasoning, and Knowledge (5 papers). Richard Moot collaborates with scholars based in France, Netherlands and South Korea. Richard Moot's co-authors include Christian Retoré, Philippe Blache, Michael Moortgat, Joan Busquets, Edward P. Stabler and Mathieu Lafourcade and has published in prestigious journals such as SHILAP Revista de lepidopterología, Lecture notes in computer science and Language Resources and Evaluation.

In The Last Decade

Richard Moot

13 papers receiving 54 citations

Peers

Richard Moot
Rob Malouf United States
Venkata Koppula United States
Richard Moot
Citations per year, relative to Richard Moot Richard Moot (= 1×) peers Ingrid Falk

Countries citing papers authored by Richard Moot

Since Specialization
Citations

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

Fields of papers citing papers by Richard Moot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Moot

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

All Works

16 of 16 papers shown
1.
Moortgat, Michael, et al.. (2023). SPINDLE: Spinning Raw Text into Lambda Terms with Graph Attention. 128–135. 1 indexed citations
2.
Moot, Richard, et al.. (2018). Polysemy, Individuation and Co-Predication: a simple solution to the counting puzzle implemented using lambda-DRT and MGL. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
3.
Lafourcade, Mathieu, et al.. (2017). Collecting Crowd-Sourced Lexical Coercions for Compositional Semantic Analysis. SPIRE - Sciences Po Institutional REpository.
4.
Moot, Richard. (2015). A type-logical treebank for French. SHILAP Revista de lepidopterología. 3(1). 2 indexed citations
5.
Moot, Richard & Christian Retoré. (2012). The Logic of Categorial Grammars. Lecture notes in computer science. 25 indexed citations
6.
Moot, Richard & Christian Retoré. (2011). Second order lambda calculus for meaning assembly: on the logical syntax of plurals. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
7.
Moot, Richard. (2010). Wide-Coverage French Syntax and Semantics using Grail. HAL (Le Centre pour la Communication Scientifique Directe). 44–47. 1 indexed citations
8.
Moot, Richard. (2010). Semi-automated Extraction of a Wide-Coverage Type-Logical Grammar for French. HAL (Le Centre pour la Communication Scientifique Directe). 189–194. 2 indexed citations
9.
Moot, Richard & Christian Retoré. (2006). Les indices pronominaux du français dans les grammaires catégorielles. Lingvisticae Investigationes. 29(1). 137–146. 1 indexed citations
10.
Blache, Philippe, Edward P. Stabler, Joan Busquets, & Richard Moot. (2005). Logical Aspects of Computational Linguistics. Lecture notes in computer science. 2 indexed citations
11.
Moot, Richard. (2004). Graph Algorithms for Improving Type-Logical Proof Search. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
12.
Moortgat, Michael & Richard Moot. (2002). Using the Spoken Dutch Corpus for type-logical grammar induction.. Language Resources and Evaluation. 2 indexed citations
13.
Moot, Richard, et al.. (2002). Proof Nets for the Multimodal Lambek Calculus. Studia Logica. 71(3). 415–442. 7 indexed citations
14.
Moortgat, Michael, et al.. (2002). Teaching tools for logic-based grammar development.
15.
Moot, Richard, et al.. (2001). Linguistic Applications of First Order Intuitionistic Linear Logic. Journal of Logic Language and Information. 10(2). 211–232. 7 indexed citations
16.
Moot, Richard, et al.. (1999). Proof nets for the multimodal Lambek calculus. TU/e Research Portal (Eindhoven University of Technology). 1096. 7 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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