Eva Gibaja

1.2k total citations · 1 hit paper
28 papers, 841 citations indexed

About

Eva Gibaja is a scholar working on Artificial Intelligence, Information Systems and Computer Science Applications. According to data from OpenAlex, Eva Gibaja has authored 28 papers receiving a total of 841 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 12 papers in Information Systems and 7 papers in Computer Science Applications. Recurrent topics in Eva Gibaja's work include Text and Document Classification Technologies (15 papers), Machine Learning and Data Classification (6 papers) and Spam and Phishing Detection (5 papers). Eva Gibaja is often cited by papers focused on Text and Document Classification Technologies (15 papers), Machine Learning and Data Classification (6 papers) and Spam and Phishing Detection (5 papers). Eva Gibaja collaborates with scholars based in Spain, United States and Saudi Arabia. Eva Gibaja's co-authors include Sebastián Ventura, Jose M. Moyano, Krzysztof J. Cios, Amelia Zafra, Alberto Cano, José María Luna, Cristóbal Romero, Francisco Romero, César Hervás‐Martínez and Waldo Fajardo and has published in prestigious journals such as Expert Systems with Applications, ACM Computing Surveys and Information Sciences.

In The Last Decade

Eva Gibaja

26 papers receiving 808 citations

Hit Papers

A Tutorial on Multilabel Learning 2015 2026 2018 2022 2015 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A Tutorial on Multilabel Learning
    2015 390 citations Eva Gibaja, Sebastián Ventura ACM Computing Surveys profile →

Peers

Eva Gibaja
Eneldo Loza Mencía Germany
Shasha Li China
Gjorgji Madjarov North Macedonia
Yiqun Zhang China
Jiaxing Zhang China
Scott Cost United States
Lun Du China
Jörg Kindermann Germany
Hamouda Chantar Libya
Sadid A. Hasan United States
Eneldo Loza Mencía Germany
Eva Gibaja
Citations per year, relative to Eva Gibaja Eva Gibaja (= 1×) peers Eneldo Loza Mencía

Countries citing papers authored by Eva Gibaja

Since Specialization
Citations

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

Fields of papers citing papers by Eva Gibaja

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eva Gibaja

This figure shows the co-authorship network connecting the top 25 collaborators of Eva Gibaja. A scholar is included among the top collaborators of Eva Gibaja 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 Eva Gibaja. Eva Gibaja 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
1.
Zafra, Amelia & Eva Gibaja. (2023). Nearest neighbor-based approaches for multi-instance multi-label classification. Expert Systems with Applications. 232. 120876–120876. 8 indexed citations
2.
Moyano, Jose M., Eva Gibaja, Krzysztof J. Cios, & Sebastián Ventura. (2020). Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms. Knowledge-Based Systems. 196. 105770–105770. 9 indexed citations
3.
Moyano, Jose M., Eva Gibaja, Krzysztof J. Cios, & Sebastián Ventura. (2020). Tree-Shaped Ensemble of Multi-Label Classifiers using Grammar-Guided Genetic Programming. 1–8. 3 indexed citations
4.
Espejo, Pedro G., Eva Gibaja, Víctor Hugo Menéndez Domínguez, Alfredo Zapata González, & Cristóbal Romero. (2019). Improving Multi-Label Classification for Learning Objects Categorization by Taking into Consideration Usage Information.. JUCS - Journal of Universal Computer Science. 25. 1687–1716. 1 indexed citations
5.
Moyano, Jose M., Eva Gibaja, Krzysztof J. Cios, & Sebastián Ventura. (2018). An evolutionary approach to build ensembles of multi-label classifiers. Information Fusion. 50. 168–180. 23 indexed citations
6.
Romero, Cristóbal, Pedro G. Espejo, Eva Gibaja, Alfredo Zapata González, & Víctor Hugo Menéndez Domínguez. (2017). Towards Automatic Classification of Learning Objects: Reducing the Number of Used Features.. Educational Data Mining. 2 indexed citations
7.
Moyano, Jose M., Eva Gibaja, Krzysztof J. Cios, & Sebastián Ventura. (2017). Review of ensembles of multi-label classifiers: Models, experimental study and prospects. Information Fusion. 44. 33–45. 105 indexed citations
8.
Moyano, Jose M., Eva Gibaja, & Sebastián Ventura. (2017). An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains. 2015–2021. 12 indexed citations
9.
Gibaja, Eva, Jose M. Moyano, & Sebastián Ventura. (2016). An ensemble-based approach for multi-view multi-label classification. Progress in Artificial Intelligence. 5(4). 251–259. 8 indexed citations
10.
Cano, Alberto, José María Luna, Eva Gibaja, & Sebastián Ventura. (2015). LAIM discretization for multi-label data. Information Sciences. 330. 370–384. 34 indexed citations
11.
Gibaja, Eva & Sebastián Ventura. (2015). A Tutorial on Multilabel Learning. ACM Computing Surveys. 47(3). 1–38. 390 indexed citations breakdown →
12.
Gibaja, Eva & Sebastián Ventura. (2014). Multi‐label learning: a review of the state of the art and ongoing research. Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery. 4(6). 411–444. 141 indexed citations
13.
Zafra, Amelia, Eva Gibaja, María Luque, & Sebastián Ventura. (2011). An evaluation of the effectiveness of e-learning system as support for traditional classes. 431–435. 10 indexed citations
14.
Gibaja, Eva, Amelia Zafra, María Luque, & Sebastián Ventura. (2011). Self-evaluation first ECTS course in a programming subject. 416–420.
15.
Gibaja, Eva, et al.. (2010). A TDIDT technique for multi-label classification. 4701. 519–524. 4 indexed citations
16.
Zafra, Amelia, Eva Gibaja, & Sebastián Ventura. (2009). Multiple Instance Learning with Multiple Objective Genetic Programming for Web Mining. Applied Soft Computing. 11(1). 93–102. 14 indexed citations
17.
Zafra, Amelia, Eva Gibaja, & Sebastián Ventura. (2008). Multiple Instance Learning with MultiObjective Genetic Programming for Web Mining. 4. 513–518. 2 indexed citations
18.
Fajardo, Waldo, et al.. (2007). An intelligent tutoring system for education by web. 522–527. 2 indexed citations
19.
Romero, Cristóbal, Sebastián Ventura, Eva Gibaja, César Hervás‐Martínez, & Francisco Romero. (2006). Web-based adaptive training simulator system for cardiac life support. Artificial Intelligence in Medicine. 38(1). 67–78. 19 indexed citations
20.
Delgado-Prieto, Miguel, et al.. (2005). BioMen: an information system to herbarium. Expert Systems with Applications. 28(3). 507–518. 6 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Eneldo Loza Mencía Breakdown of academic impact, for papers by Shasha Li Breakdown of academic impact, for papers by Gjorgji Madjarov Breakdown of academic impact, for papers by Yiqun Zhang Breakdown of academic impact, for papers by Jiaxing Zhang Breakdown of academic impact, for papers by Scott Cost Breakdown of academic impact, for papers by Lun Du Breakdown of academic impact, for papers by Jörg Kindermann Breakdown of academic impact, for papers by Hamouda Chantar Breakdown of academic impact, for papers by Sadid A. Hasan
Rankless by CCL
2026