Mihaela Vela

629 citations
28 papers · 297 indexed · h-index 9
Topics
Natural Language Processing Techniques (23 papers)Topic Modeling (19 papers)Semantic Web and Ontologies (7 papers)
Journals
SHILAP Revista de lepidopterologíaLanguage Resources and EvaluationMachine Translation

In The Last Decade

Mihaela Vela

27 papers receiving 251 citations

Peers

Mihaela Vela
Comparison fields: 5 of 36
  • Artificial Intelligence 243
  • Political Science and International Relations 68
  • Law 45
  • Language and Linguistics 32
  • Economics and Econometrics 31
Replace Daniela Tiscornia with:
Daniela Tiscornia Italy
Matthias Grabmair Germany
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Mihaela Vela relative to Daniela Tiscornia Italy Daniela Tiscornia's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mihaela Vela

Since Specialization
Citations

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

Fields of papers citing papers by Mihaela Vela

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mihaela Vela

This figure shows the co-authorship network connecting the top 25 collaborators of Mihaela Vela. A scholar is included among the top collaborators of Mihaela Vela 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 Mihaela Vela. Mihaela Vela 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
English to Manipuri and Mizo Post-Editing Effort and its Impact on Low Resource Machine Translation.
4
2 22
3 65
4 1
5 13
6
CATaLog Online: Porting a Post-editing Tool to the Web.
7
7
SubCo: A Learner Translation Corpus of Human and Machine Subtitles.
2
8 3
9 24
10 2
11 24
12
Re-assessing the WMT2013 Human Evaluation with Professional Translators Trainees
4
13
CATaLog: New Approaches to TM and Post Editing Interfaces
7
14
Can Translation Memories afford not to use paraphrasing
6
15 8
16 21
17 7
18
Generic NLP Tools for Supporting Shallow Ontology Building
2
19 23
20
Automated Analysis of Planktic Foraminifers Part III: Neural Network Classification
1

About Mihaela Vela

Mihaela Vela is a scholar working on Artificial Intelligence, Language and Linguistics and Law, having authored 28 papers that have together received 297 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (23 papers), Topic Modeling (19 papers) and Semantic Web and Ontologies (7 papers). The work is most often cited by research in Artificial Intelligence (243 citations), Law (45 citations) and Language and Linguistics (32 citations). Mihaela Vela has collaborated with scholars based in Germany, India and United Kingdom. Frequent co-authors include Josef van Genabith, Marcos Zampieri, Santanu Pal, Sudip Kumar Naskar, Silvia Hansen‐Schirra, Stella Neumann, Artuur Leeuwenberg, Thierry Declerck, Liling Tan and Antonio Krüger. Their work appears in journals such as SHILAP Revista de lepidopterología, Language Resources and Evaluation 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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