What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Data mining
His main research concerns Educational data mining, Data science, Artificial intelligence, Association rule learning and Machine learning.
His studies deal with areas such as Anomaly detection and Data mining as well as Educational data mining.
His Data science research is multidisciplinary, incorporating perspectives in Field, Concept mining, Web mining and Visualization.
His Association rule learning research includes themes of Learning Management, Collaborative filtering and Cluster analysis.
Cristóbal Romero works mostly in the field of Machine learning, limiting it down to topics relating to Usage data and, in certain cases, Classifier, E-learning and Recommender system.
His Genetic programming study combines topics from a wide range of disciplines, such as Evolutionary algorithm, High dimensional and Knowledge extraction.
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?
Cristóbal Romero mainly focuses on Artificial intelligence, Machine learning, Educational data mining, Data science and Data mining.
In Artificial intelligence, Cristóbal Romero works on issues like Usage data, which are connected to Classifier and Data mining algorithm.
The study incorporates disciplines such as Preprocessor and Knowledge extraction in addition to Machine learning.
His biological study spans a wide range of topics, including Learning Management, Learning analytics, Web mining and Library science.
His work is dedicated to discovering how Data science, Collaborative learning are connected with Educational technology and other disciplines.
He has researched Association rule learning in several fields, including Class, Instructional design and Virtual learning environment, World Wide Web.
He most often published in these fields:
- Artificial intelligence (39.34%)
- Machine learning (31.15%)
- Educational data mining (31.97%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial intelligence (39.34%)
- Educational data mining (31.97%)
- Machine learning (31.15%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Educational data mining, Machine learning, Blended learning and Data science.
His research on Artificial intelligence frequently links to adjacent areas such as Natural language processing.
His research integrates issues of Learning analytics and World Wide Web in his study of Educational data mining.
His work on Sensor fusion, Statistical classification, Predictive modelling and Genetic algorithm as part of general Machine learning study is frequently connected to Multi criteria, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Blended learning research is multidisciplinary, relying on both Educational assessment, Game based learning, Distance education and Library science.
In his works, he conducts interdisciplinary research on Data science and Process mining.
Between 2016 and 2021, his most popular works were:
- A survey on educational process mining (57 citations)
- Educational data science in massive open online courses (43 citations)
- Educational data mining and learning analytics: An updated survey (35 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Programming language
His primary areas of study are Data science, Process, World Wide Web, Learning analytics and Educational data mining.
His Data science study incorporates themes from Text mining and Event.
His Process research spans across into fields like Data mining and Management system.
His work in the fields of Thesaurus and Massive open online course overlaps with other areas such as Skepticism and Application areas.
Cristóbal Romero has included themes like Set, Cluster analysis, Interface, Knowledge extraction and Analytics in his Learning analytics study.
His Educational data mining study integrates concerns from other disciplines, such as Domain, Field, Graph and Representation.
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