1.7k total citations 24 papers, 960 citations indexed
About
Terence Parr is a scholar working on Artificial Intelligence, Information Systems and Software.
According to data from OpenAlex, Terence Parr has authored 24 papers receiving a total of 960 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Artificial Intelligence, 7 papers in Information Systems and 5 papers in Software. Recurrent topics in Terence Parr's work include Natural Language Processing Techniques (6 papers), Software Engineering Research (5 papers) and Logic, programming, and type systems (5 papers). Terence Parr is often cited by papers focused on Natural Language Processing Techniques (6 papers), Software Engineering Research (5 papers) and Logic, programming, and type systems (5 papers). Terence Parr collaborates with scholars based in United States and Netherlands. Terence Parr's co-authors include Kathleen Fisher, James Wilson, Jurgen Vinju, H. G. Dietz, Russell W. Quong, Kathleen Fisher, Paul R. Woodward and Matthew O’Keefe and has published in prestigious journals such as SHILAP Revista de lepidopterología, Information Sciences and ACM SIGPLAN Notices.
Citations per year, relative to Terence Parr Terence Parr (= 1×)
peers
Ketil Stølen
Countries citing papers authored by Terence Parr
Since
Specialization
Citations
This map shows the geographic impact of Terence Parr'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 Terence Parr with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Terence Parr more than expected).
This network shows the impact of papers produced by Terence Parr. 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 Terence Parr. The network helps show where Terence Parr may publish in the future.
Co-authorship network of co-authors of Terence Parr
This figure shows the co-authorship network connecting the top 25 collaborators of Terence Parr.
A scholar is included among the top collaborators of Terence Parr 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 Terence Parr. Terence Parr is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Parr, Terence & James Wilson. (2019). Technical Report: A Stratification Approach to Partial Dependence for Codependent Variables. arXiv (Cornell University).2 indexed citations
4.
Parr, Terence & James Wilson. (2019). A Stratification Approach to Partial Dependence for Codependent Variables. arXiv (Cornell University).1 indexed citations
5.
Parr, Terence & Jurgen Vinju. (2016). Towards a universal code formatter through machine learning. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 137–151.15 indexed citations
Parr, Terence. (2009). Language Implementation Patterns: Create Your Own Domain-Specific and General Programming Languages. CERN Document Server (European Organization for Nuclear Research).30 indexed citations
Parr, Terence. (2007). The Definitive ANTLR Reference: Building Domain-Specific Languages. CERN Document Server (European Organization for Nuclear Research).254 indexed citations
Parr, Terence. (1999). Language Translation Using PCCTS and C.25 indexed citations
19.
Parr, Terence. (1993). Obtaining practical variants of LL (K) and LR (K) for K greater than 1 by splitting the atomic K-tuple. Purdue e-Pubs (Purdue University System).6 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
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Rankless may not fully capture the entirety of a scholar's output or impact.