Pedro G. Espejo

1.3k citations
6 papers · 855 indexed · 1 hit paper · h-index 3
Topics
Educational Technology and Assessment (3 papers)Online Learning and Analytics (2 papers)Advanced Data Processing Techniques (1 paper)
Journals
Computer Applications in Engineering EducationJUCS - Journal of Universal Computer ScienceIEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)

In The Last Decade

Pedro G. Espejo

5 papers receiving 762 citations

Hit Papers

A Survey on the Application of Genetic Programming to Cla...20092026201420202009100200300400

Peers

Pedro G. Espejo
Comparison fields: 5 of 83
  • Artificial Intelligence 507
  • Computer Science Applications 389
  • Information Systems 219
  • Education 91
  • Computer Networks and Communications 84
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Citations per field
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Citations per year

Countries citing papers authored by Pedro G. Espejo

Since Specialization
Citations

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

Fields of papers citing papers by Pedro G. Espejo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pedro G. Espejo. 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 Pedro G. Espejo. The network helps show where Pedro G. Espejo may publish in the future.

Co-authorship network of co-authors of Pedro G. Espejo

This figure shows the co-authorship network connecting the top 25 collaborators of Pedro G. Espejo. A scholar is included among the top collaborators of Pedro G. Espejo 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 Pedro G. Espejo. Pedro G. Espejo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

6 of 6 papers shown
#WorkIndexed citations
1
Improving Multi-Label Classification for Learning Objects Categorization by Taking into Consideration Usage Information.
1
2 0
3
Towards Automatic Classification of Learning Objects: Reducing the Number of Used Features.
2
4 208
5
A Survey on the Application of Genetic Programming to Classificationbreakdown →
400
6
Data Mining Algorithms to Classify Students
244

About Pedro G. Espejo

Pedro G. Espejo is a scholar working on Computer Science Applications, Information Systems and Control and Systems Engineering, having authored 6 papers that have together received 855 indexed citations. Recurring topics across this work include Educational Technology and Assessment (3 papers), Online Learning and Analytics (2 papers) and Advanced Data Processing Techniques (1 paper). The work is most often cited by research in Computer Science Applications (389 citations), Artificial Intelligence (507 citations) and Information Systems (219 citations). Pedro G. Espejo has collaborated with scholars based in Spain, United States and Switzerland. Frequent co-authors include Sebastián Ventura, Francisco Herrera, Cristóbal Romero, César Hervás‐Martínez, José Raúl Romero, Amelia Zafra, Alfredo Zapata González, Víctor Hugo Menéndez Domínguez, Eva Gibaja and Alejandro Bogarín. Their work appears in journals such as Computer Applications in Engineering Education, JUCS - Journal of Universal Computer Science and IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews).

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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