Fernando Berzal

2.1k citations
48 papers · 1.2k indexed · 1 hit paper · h-index 14

Fernando Berzal

46 papers receiving 1.1k citations

Hit Papers

A Survey of Link Prediction in Complex Networks4442016202620192022100200300400

Peers

Fernando Berzal
Comparison fields: 5 of 96
  • Statistical and Nonlinear Physics 367
  • Artificial Intelligence 725
  • Signal Processing 224
  • Information Systems 415
  • 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

The 17 scholars most cited alongside Fernando Berzal, 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 Fernando Berzal Line = papers co-authored together Fernando Berzal links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20195
2 201532
3 20122
4 20121
5
LAMB - A Lexical Analyzer with Ambiguity Support
20112
6 201110
7 20106
8 20101
9 200715
10 20061
11 20063
12
Development of applications with fuzzy objects in modern programming platforms: Research Articles
20054
13 20051
14
Association rule evaluation for classification purposes
20057
15 20050
16
Usability Issues in Data Mining Systems.
20032
17 200343
18 20022
19 200224
20 20029

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), Data Management and Algorithms (12 papers), Advanced Database Systems and Queries (8 papers), Model-Driven Software Engineering Techniques (5 papers), Natural Language Processing Techniques (5 papers), Algorithms and Data Compression (5 papers) and Complex Network Analysis Techniques (4 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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