Jaume Baixeries

454 citations
18 papers · 176 · h-index 8

Impact in

Papers in

Jaume Baixeries

15 papers receiving 165 citations

Peers

Jaume Baixeries
Comparison fields: 5 of 49
  • Developmental Biology 20
  • Cultural Studies 42
  • Artificial Intelligence 76
  • Linguistics and Language 9
  • Language and Linguistics 20
Replace Łukasz Dębowski with:
Łukasz Dębowski Poland
Gemma Bel-Enguix Mexico
Paola Merlo Switzerland
Dimitrios Alikaniotis United Kingdom
Beate Dorow Germany
Miikka Silfverberg United States
Alexander Clark United Kingdom
George Kingsley Zipf
Roland Hausser Germany
John K. Pate Australia
Jaume Baixeries relative to Łukasz Dębowski Poland Łukasz Dębowski's profile →
Citations per field
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Łukasz Dębowski · 1×
Citations per year

Countries citing papers authored by Jaume Baixeries

Since Specialization
Citations

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

Fields of papers citing papers by Jaume Baixeries

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Jaume Baixeries, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jaume Baixeries Line = papers co-authored together Jaume Baixeries links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 201349
2 201423
3
The challenges of statistical patterns of language: the case of Menzerath's law in genomes
201323
4 201117
5 201315
6 202214
7 201111
8 20159
9 20215
10 20242
11 20142
12 20182
13 20122
14
When is Menzerath-Altmann law mathematically trivial? A new test
20121
15
Sampling strategies for finding frequent sets
20031
16 20240
17
When is Menzerath-Altmann law mathematically trivial?
20120
18 20250

About Jaume Baixeries

Jaume Baixeries is a scholar working on Molecular Biology, Artificial Intelligence, Signal Processing, Computational Theory and Mathematics and Genetics, having authored 18 papers that have together received 176 indexed citations. Recurring topics across this work include Fractal and DNA sequence analysis (4 papers), Rough Sets and Fuzzy Logic (3 papers), Data Management and Algorithms (3 papers), RNA and protein synthesis mechanisms (2 papers), Language and cultural evolution (2 papers), Authorship Attribution and Profiling (2 papers), Data Quality and Management (2 papers) and Natural Language Processing Techniques (2 papers). The work is most often cited by research in Developmental Biology (20 citations), Cultural Studies (42 citations), Artificial Intelligence (76 citations), Linguistics and Language (9 citations) and Language and Linguistics (20 citations). Jaume Baixeries has collaborated with scholars based in Spain, France and Norway. Frequent co-authors include Ramon Ferrer‐i‐Cancho, Antoni Hernández-Fernändez, Brita Elvevåg, Núria Forns, Amedeo Napoli, Mehdi Kaytoue, Ricard Gavaldà, Xiao Zhang, Gemma Bel-Enguix and Manuel Ojeda‐Aciego. Their work appears in journals such as Languages, Journal of Quantitative Linguistics, PLoS ONE, Biosystems and International Journal of Approximate Reasoning.

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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