Kim Luyckx

776 total citations
24 papers, 473 citations indexed

About

Kim Luyckx is a scholar working on Artificial Intelligence, Molecular Biology and Surgery. According to data from OpenAlex, Kim Luyckx has authored 24 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 6 papers in Molecular Biology and 2 papers in Surgery. Recurrent topics in Kim Luyckx's work include Authorship Attribution and Profiling (13 papers), Topic Modeling (13 papers) and Natural Language Processing Techniques (7 papers). Kim Luyckx is often cited by papers focused on Authorship Attribution and Profiling (13 papers), Topic Modeling (13 papers) and Natural Language Processing Techniques (7 papers). Kim Luyckx collaborates with scholars based in Belgium and Netherlands. Kim Luyckx's co-authors include Walter Daelemans, Mike Kestemont, Tim Van den Bulcke, Madhumita Sushil, Boris Čule, Claudia Peersman, Ineke Tieken, Undine Samuel, Johan De Meester and Guy De Pauw and has published in prestigious journals such as Journal of the American Medical Informatics Association, Nephrology Dialysis Transplantation and Eurosurveillance.

In The Last Decade

Kim Luyckx

24 papers receiving 413 citations

Peers

Kim Luyckx
Comparison fields: 5 of 72
  • Artificial Intelligence 400
  • Molecular Biology 70
  • Information Systems 50
  • Health Information Management 43
  • Sociology and Political Science 33
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Citations per field, relative to Kim Luyckx
Kim Luyckx · 1×
Citations per year, relative to Kim Luyckx
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Countries citing papers authored by Kim Luyckx

Since Specialization
Citations

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

Fields of papers citing papers by Kim Luyckx

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kim Luyckx

This figure shows the co-authorship network connecting the top 25 collaborators of Kim Luyckx. A scholar is included among the top collaborators of Kim Luyckx 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 Kim Luyckx. Kim Luyckx 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 15
2 27
3 35
4 16
5 7
6 52
7 3
8
De-Identification of Clinical Free Text in Dutch with Limited Training Data: A Case Study
5
9
The Netlog Corpus. A Resource for the Study of Flemish Dutch Internet Language
5
10 20
11
Evaluating unmasking for cross-genre authorship verification
1
12 36
13
Intrinsic Plagiarism Detection Using Character Trigram Distance Scores Notebook for PAN at CLEF 2011
6
14
Intrinsic plagiarism detection using character trigram distance scores
14
15
Scalability Issues in Authorship Attribution
28
16
Personae: a Corpus for Author and Personality Prediction from Text.
37
17 90
18
Stylogenetics: Clustering-based stylistic analysis of literary corpora
21
19
Shallow Text Analysis and Machine Learning for Authorship Attribution
26
20
Shallow Text Analysis and Machine Learning for Authorship Attribtion.
6

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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