Rafael Berlanga

89 papers receiving 1.1k citations

Peers

Rafael Berlanga
Comparison fields: 5 of 97
  • Artificial Intelligence 943
  • Information Systems 421
  • Computer Networks and Communications 313
  • Molecular Biology 292
  • Management Science and Operations Research 267
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Claudia d’Amato Italy
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Countries citing papers authored by Rafael Berlanga

Since Specialization
Citations

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

Fields of papers citing papers by Rafael Berlanga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rafael Berlanga

This figure shows the co-authorship network connecting the top 25 collaborators of Rafael Berlanga. A scholar is included among the top collaborators of Rafael Berlanga 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 Rafael Berlanga. Rafael Berlanga 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 1
2 27
3 10
4 9
5
OBJECTMINER: A NEW APPROACH FOR MINING COMPLEX OBJECTS
4
6 2
7
A framework for obtaining structurally complex condensed representations of document sets in the biomedical domain
2
8
A clustering-based approach for unsupervised word sense disambiguation
10
9
Learning a Statistical Model of Product Aspects for Sentiment Analysis
1
10
Methodology for lubricant selection in deep drawing steel process for the automotive industry, a new development and validation
2
11
Semantic annotation of biomedical texts through concept retrieval
16
12
Building Ontologies Collaboratively Using ContentCVS
8
13
ContentCVS: A CVS-based Collaborative ONTology ENgineering Tool.
5
14
Towards a Logic−based Assessment of the compatibility of UMLS sources
3
15
Measure Assessment for Heterogeneous XML Collections.
1
16
Use of Shared Lexical Resources for Efficient Ontological Engineering.
3
17
Temporal-Semantic Clustering of Newspaper Articles for Event Detection
3
18
Un algoritmo incremental para la obtención de cubrimientos con datos mezclados
3
19
Retrieval of Information from Temporal Document Databases
4
20
Modelling Periodicals with an Extended Object Oriented Data Model.
1

About Rafael Berlanga

Rafael Berlanga is a scholar working on Artificial Intelligence, Information Systems and Management Science and Operations Research, having authored 95 papers that have together received 1.3k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (60 papers), Biomedical Text Mining and Ontologies (28 papers) and Advanced Database Systems and Queries (21 papers). The work is most often cited by research in Artificial Intelligence (943 citations), Management Science and Operations Research (267 citations) and Information Systems (421 citations). Rafael Berlanga has collaborated with scholars based in Spain, United Kingdom and Denmark. Frequent co-authors include Victoria Nebot, María José Aramburu, Torben Bach Pedersen, Ernesto Jiménez-Ruiz, Antonio Jimeno Yepes, Juan Manuel Pérez, Aurora Pons-Porrata, Dietrich Rebholz‐Schuhmann, Bernardo Cuenca Grau and José Ruíz-Shulcloper. Their work appears in journals such as BMC Bioinformatics, Information Sciences and International Journal of Environmental Research and Public Health.

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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