Pavel Brazdil

5.0k citations
67 papers · 2.0k indexed · h-index 19
Topics
Machine Learning and Data Classification (20 papers)Advanced Text Analysis Techniques (13 papers)Machine Learning and Algorithms (10 papers)
Journals
SHILAP Revista de lepidopterologíaNeurocomputingMachine Learning

In The Last Decade

Pavel Brazdil

63 papers receiving 1.9k citations

Peers

Pavel Brazdil
Comparison fields: 5 of 157
  • Artificial Intelligence 1.5k
  • Information Systems 318
  • Computer Vision and Pattern Recognition 259
  • Computational Theory and Mathematics 243
  • Management Science and Operations Research 145
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José A. Gámez Spain
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Ivana Strumberger Serbia
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Citations per field
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Citations per year

Countries citing papers authored by Pavel Brazdil

Since Specialization
Citations

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

Fields of papers citing papers by Pavel Brazdil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pavel Brazdil

This figure shows the co-authorship network connecting the top 25 collaborators of Pavel Brazdil. A scholar is included among the top collaborators of Pavel Brazdil 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 Pavel Brazdil. Pavel Brazdil 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 2
2
Algorithm selection via meta-learning and sample-based active testing
9
3 3
4 77
5 6
6 1
7 280
8 1
9 6
10
Learning Paraphrases from WNS Corpora.
4
11 6
12
Machine Learning: ECML 2005: 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005, Proceedings (Lecture Notes in Computer Science ... / Lecture Notes in Artificial Intelligence)
1
13
Machine learning : ECML 2005 : 16th European Conference on Machine Learning, Porto, Portugal, October 3-7, 2005 : proceedings
12
14
Improved data set characterisation for meta-learning
9
15
Learning by Refining Algorithm Sketches
3
16
Knowledge Integration and Learning
0
17 22
18
Use of derivation trees in discrimination
0
19
Experimental Learning Model.
14
20 2

About Pavel Brazdil

Pavel Brazdil is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics, having authored 67 papers that have together received 2.0k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (20 papers), Advanced Text Analysis Techniques (13 papers) and Machine Learning and Algorithms (10 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Computational Theory and Mathematics (243 citations) and Information Systems (318 citations). Pavel Brazdil has collaborated with scholars based in Portugal, Netherlands and United States. Frequent co-authors include Carlos Soares, Christophe Giraud-Carrier, Ricardo Vilalta, João Gama, Joaquim Pinto da Costa, Alí­pio Jorge, Joaquin Vanschoren, Rui Camacho, Luı́s Torgo and Jan N. van Rijn. Their work appears in journals such as SHILAP Revista de lepidopterología, Neurocomputing and Machine Learning.

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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