H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 54 Citations 18,753 230 World Ranking 2357 National Ranking 26

Research.com Recognitions

Awards & Achievements

2013 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Programming language

His primary scientific interests are in Artificial intelligence, Machine learning, Data mining, Educational data mining and Data science. His work deals with themes such as Virtual learning environment and Computation, which intersect with Artificial intelligence. His research in Machine learning tackles topics such as Usage data which are related to areas like Data mining algorithm, Classifier and E-learning.

His research in Data mining intersects with topics in Relevance, Errors-in-variables models and Feature selection. His studies in Data science integrate themes in fields like Association rule learning, Field, Data type and Web mining. His biological study spans a wide range of topics, including Learning Management and World Wide Web.

His most cited work include:

  • Educational Data Mining: A Review of the State of the Art (1189 citations)
  • Educational data mining: A survey from 1995 to 2005 (935 citations)
  • KEEL: a software tool to assess evolutionary algorithms for data mining problems (907 citations)

What are the main themes of his work throughout his whole career to date?

Sebastián Ventura mainly investigates Artificial intelligence, Machine learning, Data mining, Genetic programming and Association rule learning. Sebastián Ventura combines subjects such as Set and Pattern recognition with his study of Artificial intelligence. His study brings together the fields of Algorithm and Machine learning.

His work on Knowledge extraction as part of general Data mining study is frequently linked to Spark, therefore connecting diverse disciplines of science. His studies deal with areas such as Population-based incremental learning and Web mining as well as Genetic programming. The various areas that he examines in his Association rule learning study include Learning Management, Task, Data science and Big data.

He most often published in these fields:

  • Artificial intelligence (59.25%)
  • Machine learning (49.81%)
  • Data mining (37.36%)

What were the highlights of his more recent work (between 2016-2021)?

  • Artificial intelligence (59.25%)
  • Machine learning (49.81%)
  • Data mining (37.36%)

In recent papers he was focusing on the following fields of study:

His scientific interests lie mostly in Artificial intelligence, Machine learning, Data mining, Association rule learning and Evolutionary algorithm. His Artificial intelligence research includes themes of Computational complexity theory and Pattern recognition. His work in Machine learning tackles topics such as Representation which are related to areas like Cluster analysis, Genetic algorithm, Feature vector and Task analysis.

The study incorporates disciplines such as Computational intelligence and Set in addition to Data mining. His Association rule learning research incorporates themes from Field, Data science and Big data. His study in Evolutionary algorithm is interdisciplinary in nature, drawing from both Evolutionary computation, Software architecture, Project management and Fitness function.

Between 2016 and 2021, his most popular works were:

  • Multi-Target Support Vector Regression Via Correlation Regressor Chains (61 citations)
  • Multi-Target Support Vector Regression Via Correlation Regressor Chains (61 citations)
  • Review of ensembles of multi-label classifiers: Models, experimental study and prospects (45 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Programming language

Sebastián Ventura mostly deals with Artificial intelligence, Machine learning, Data mining, Association rule learning and Active learning. Sebastián Ventura incorporates Artificial intelligence and Process in his studies. His work in the fields of Machine learning, such as Curse of dimensionality, Errors-in-variables models and Support vector machine, overlaps with other areas such as Statistical hypothesis testing.

Sebastián Ventura has included themes like Tree and k-nearest neighbors algorithm in his Data mining study. His study on Association rule learning also encompasses disciplines like

  • Data science which is related to area like Big data,
  • Genetic programming and related Natural language processing, Visualization and Data visualization. He interconnects Evolutionary algorithm, Active learning and Set in the investigation of issues within Active learning.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Educational Data Mining: A Review of the State of the Art

Cristóbal Romero;Sebastián Ventura.
systems man and cybernetics (2010)

2195 Citations

Educational data mining: A survey from 1995 to 2005

C. Romero;S. Ventura.
Expert Systems With Applications (2007)

2017 Citations

Data mining in course management systems: Moodle case study and tutorial

Cristóbal Romero;Sebastián Ventura;Enrique García.
Computer Education (2008)

1449 Citations

KEEL: a software tool to assess evolutionary algorithms for data mining problems

J. Alcalá-Fdez;L. Sánchez;S. García;M. J. del Jesus.
soft computing (2008)

1209 Citations

Data mining in education

Cristobal Romero;Sebastian Ventura.
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (2013)

868 Citations

A Survey on the Application of Genetic Programming to Classification

P.G. Espejo;S. Ventura;F. Herrera.
systems man and cybernetics (2010)

541 Citations

Predicting students' final performance from participation in on-line discussion forums

Cristóbal Romero;Manuel-Ignacio López;Jose-María Luna;Sebastián Ventura.
Computer Education (2013)

541 Citations

Handbook of Educational Data Mining

Cristobal Romero;Sebastian Ventura;Mykola Pechenizkiy;Ryan S.J.d. Baker.
Chapman and Hall/CRC data mining and knowledge discovery series (2010)

501 Citations

Data Mining Algorithms to Classify Students

Cristóbal Romero;Sebastián Ventura;Pedro G. Espejo;César Hervás.
educational data mining (2008)

498 Citations

A Tutorial on Multilabel Learning

Eva Gibaja;Sebastián Ventura.
ACM Computing Surveys (2015)

372 Citations

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