Nicola Ueffing

25 papers receiving 1.0k citations

Peers

Nicola Ueffing
Comparison fields: 5 of 43
  • Artificial Intelligence 1.2k
  • Computer Vision and Pattern Recognition 115
  • Information Systems 90
  • Computational Theory and Mathematics 86
  • Computer Networks and Communications 81
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Yaacov Choueka Israel
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Citations per field
00.5×10×12.6×
Yaacov Choueka · 1×
Citations per year

Countries citing papers authored by Nicola Ueffing

Since Specialization
Citations

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

Fields of papers citing papers by Nicola Ueffing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nicola Ueffing

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 4
2
Automatic Post-Editing and Machine Translation Quality Estimation at eBay
1
3 40
4
Transductive learning for statistical machine translation
74
5 28
6 82
7 24
8
Using monolingual source-language data to improve MT performance.
22
9 82
10
Computing Consensus Translation for Multiple Machine Translation Systems Using Enhanced Hypothesis Alignment
127
11
Preprocessing and Normalization for Automatic Evaluation of Machine Translation
10
12
Application of word-level confidence measures in interactive statistical machine translation
29
13 26
14
Restricted edge-connectivity and minimum edge-degree.
24
15 7
16 27
17
Confidence measures for statistical machine translation
34
18
A novel string-to-string distance measure with applications to machine translation evaluation
51
19 56
20 60

About Nicola Ueffing

Nicola Ueffing is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications, having authored 25 papers that have together received 1.3k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (23 papers), Topic Modeling (22 papers) and Speech and dialogue systems (6 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Computer Vision and Pattern Recognition (115 citations) and Computational Theory and Mathematics (86 citations). Nicola Ueffing has collaborated with scholars based in Germany, Canada and United States. Frequent co-authors include Hermann Ney, Gregor Leusch, Franz Josef Och, Evgeny Matusov, George Foster, Gholamreza Haffari, Anoop Sarkar, Alberto Sanchís, Erin Fitzgerald and Simona Gandrabur. Their work appears in journals such as Computational Linguistics, Discrete Mathematics and Machine Translation.

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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