This map shows the geographic impact of Andy Way'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 Andy Way with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andy Way more than expected).
This network shows the impact of papers produced by Andy Way. 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 Andy Way. The network helps show where Andy Way may publish in the future.
Co-authorship network of co-authors of Andy Way
This figure shows the co-authorship network connecting the top 25 collaborators of Andy Way.
A scholar is included among the top collaborators of Andy Way 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 Andy Way. Andy Way is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Poncelas, Alberto, et al.. (2020). The impact of indirect machine translation on sentiment classification. Dublin City University Open Access Institutional Repository (Dublin City University).1 indexed citations
7.
Passban, Peyman, Qun Liu, & Andy Way. (2018). Improving character-based decoding using target-side morphological\ninformation for neural machine translation. Arrow@dit (Dublin Institute of Technology).9 indexed citations
8.
Du, Jinhua & Andy Way. (2017). Neural pre-translation for hybrid machine translation. Arrow@dit (Dublin Institute of Technology).7 indexed citations
9.
Vanmassenhove, Eva, Jinhua Du, & Andy Way. (2016). Improving subject-verb agreement in SMT. Arrow@dit (Dublin Institute of Technology).2 indexed citations
10.
Afli, Haithem, et al.. (2016). Using SMT for OCR error correction of historical texts.25 indexed citations
11.
Moorkens, Joss, David Lewis, Wessel Reijers, Eva Vanmassenhove, & Andy Way. (2016). Translation resources and translator disempowerment. Arrow@dit (Dublin Institute of Technology).8 indexed citations
12.
Du, Jinhua, et al.. (2016). Using BabelNet to improve OOV coverage in SMT.7 indexed citations
13.
Jiang, Jie, et al.. (2010). The DCU machine translation systems for IWSLT 2010. Arrow@dit (Dublin Institute of Technology).1 indexed citations
14.
Hassan, Hany, Khalil Sima’an, & Andy Way. (2009). Lexicalized Semi-Incremental Dependency Parsing. UvA-DARE (University of Amsterdam).6 indexed citations
15.
Owczarzak, Karolina, Josef van Genabith, Yvette Graham, & Andy Way. (2007). Using F-structures in machine translation evaluation. Arrow@dit (Dublin Institute of Technology).1 indexed citations
16.
Owczarzak, Karolina, et al.. (2005). Improving Online Machine Translation Systems. Arrow@dit (Dublin Institute of Technology).6 indexed citations
17.
Judge, John, Michael Burke, Aoife Cahill, et al.. (2005). Strong Domain Variation and Treebank-Induced LFG Resources. Arrow@dit (Dublin Institute of Technology).3 indexed citations
18.
Way, Andy, et al.. (2004). Example-Based Controlled Translation. Arrow@dit (Dublin Institute of Technology).11 indexed citations
19.
Cahill, Aoife, et al.. (2003). Quasi-Logical Forms from F-Structures for the Penn Treebank. Arrow@dit (Dublin Institute of Technology).3 indexed citations
20.
Way, Andy. (2001). Translating with examples. Dublin City University Open Access Institutional Repository (Dublin City University).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.