2013 - ACM Senior Member
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.
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.
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.
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
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Educational Data Mining: A Review of the State of the Art
Cristóbal Romero;Sebastián Ventura.
systems man and cybernetics (2010)
Educational data mining: A survey from 1995 to 2005
C. Romero;S. Ventura.
Expert Systems With Applications (2007)
Data mining in course management systems: Moodle case study and tutorial
Cristóbal Romero;Sebastián Ventura;Enrique García.
Computer Education (2008)
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)
Data mining in education
Cristobal Romero;Sebastian Ventura.
Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery (2013)
Predicting students' final performance from participation in on-line discussion forums
Cristóbal Romero;Manuel-Ignacio López;Jose-María Luna;Sebastián Ventura.
Computer Education (2013)
A Survey on the Application of Genetic Programming to Classification
P.G. Espejo;S. Ventura;F. Herrera.
systems man and cybernetics (2010)
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)
Data Mining Algorithms to Classify Students
Cristóbal Romero;Sebastián Ventura;Pedro G. Espejo;César Hervás.
educational data mining (2008)
A Tutorial on Multilabel Learning
Eva Gibaja;Sebastián Ventura.
ACM Computing Surveys (2015)
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