Luísa Coheur

1.3k total citations
68 papers, 689 citations indexed

About

Luísa Coheur is a scholar working on Artificial Intelligence, Human-Computer Interaction and Social Psychology. According to data from OpenAlex, Luísa Coheur has authored 68 papers receiving a total of 689 indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Artificial Intelligence, 6 papers in Human-Computer Interaction and 5 papers in Social Psychology. Recurrent topics in Luísa Coheur's work include Natural Language Processing Techniques (46 papers), Topic Modeling (43 papers) and Speech and dialogue systems (19 papers). Luísa Coheur is often cited by papers focused on Natural Language Processing Techniques (46 papers), Topic Modeling (43 papers) and Speech and dialogue systems (19 papers). Luísa Coheur collaborates with scholars based in Portugal, United States and Brazil. Luísa Coheur's co-authors include João Paulo Carvalho, Ana Cristina Mendes, Ricardo Ribeiro, Hugo Rosa, Andreas Wichert, João Silva, Isabel Trancoso, Paula Costa Ferreira, Ana Margarida Veiga Simão and Paula Paulino and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and IEEE Access.

In The Last Decade

Luísa Coheur

61 papers receiving 639 citations

Peers

Luísa Coheur
Comparison fields: 5 of 65
  • Artificial Intelligence 596
  • Social Psychology 176
  • Information Systems 103
  • Signal Processing 91
  • Sociology and Political Science 45
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Citations per field, relative to Luísa Coheur
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Citations per year, relative to Luísa Coheur
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Countries citing papers authored by Luísa Coheur

Since Specialization
Citations

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

Fields of papers citing papers by Luísa Coheur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Luísa Coheur

This figure shows the co-authorship network connecting the top 25 collaborators of Luísa Coheur. A scholar is included among the top collaborators of Luísa Coheur 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 Luísa Coheur. Luísa Coheur 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
# Work Indexed citations
1 0
2 8
3 4
4
PE2LGP Animator: A Tool To Animate A Portuguese Sign Language Avatar
3
5 0
6 10
7 2
8 2
9 0
10
Translation errors from English to Portuguese: an annotated corpus
2
11
Meet EDGAR, a tutoring agent at MONSERRATE
3
12
Dealing with unknown words in statistical machine translation
2
13
An English-Portuguese parallel corpus of questions: translation guidelines and application in SMT
5
14 3
15
Named entity translation using anchor texts.
7
16 7
17
Named Entity Recognition in Questions: Towards a Golden Collection
5
18
Towards a General and Extensible Phrase-Extraction Algorithm
11
19
Building a Golden Collection of Parallel Multi-Language Word Alignment
25
20
The INESC-ID IWSLT07 SMT System
1

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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