Fernando Berzal

46 papers receiving 1.1k citations

Hit Papers

A Survey of Link Prediction in Complex Networks20162026201920222016100200300400

Peers

Fernando Berzal
Comparison fields: 5 of 96
  • Artificial Intelligence 725
  • Information Systems 415
  • Statistical and Nonlinear Physics 367
  • Computer Networks and Communications 262
  • Computational Theory and Mathematics 242
Replace S. P. Rajagopalan with:
S. P. Rajagopalan India
Peixiang Zhao United States
Francesco Gullo Italy
Parag Singla India
Glen Jeh United States
Pierre Senellart France
Jason Y. Zien United States
Claudio Lucchese Italy
Daixin Wang China
Ali Dasdan United States
Fernando Berzal relative to S. P. Rajagopalan India S. P. Rajagopalan's profile →
Citations per field
00.5×2.6×
S. P. Rajagopalan · 1×
Citations per year

Countries citing papers authored by Fernando Berzal

Since Specialization
Citations

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

Fields of papers citing papers by Fernando Berzal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Berzal

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Berzal. A scholar is included among the top collaborators of Fernando Berzal 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 Fernando Berzal. Fernando Berzal 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 5
2 32
3 2
4 1
5
LAMB - A Lexical Analyzer with Ambiguity Support
2
6 10
7 6
8 1
9 15
10 1
11 3
12
Development of applications with fuzzy objects in modern programming platforms: Research Articles
4
13 1
14
Association rule evaluation for classification purposes
7
15 0
16
Usability Issues in Data Mining Systems.
2
17 43
18 2
19 24
20 9

About Fernando Berzal

Fernando Berzal is a scholar working on Software, Signal Processing and Information Systems, having authored 48 papers that have together received 1.2k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (18 papers), Rough Sets and Fuzzy Logic (13 papers) and Data Management and Algorithms (12 papers). The work is most often cited by research in Statistical and Nonlinear Physics (367 citations), Artificial Intelligence (725 citations) and Signal Processing (224 citations). Fernando Berzal has collaborated with scholars based in Spain, Ireland and Poland. Frequent co-authors include Juan-Carlos Cubero, Víctor Martínez, Nicolás Marı́n, Daniel Sánchez, M.A. Vila, Ignacio J. Blanco, José-Marı́a Serrano, Marı́a J. Martı́n-Bautista, Olga Pons and Sławomir Zadrożny. Their work appears in journals such as Communications of the ACM, Expert Systems with Applications and ACM Computing Surveys.

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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