What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- World Wide Web
- The Internet
Geert-Jan Houben focuses on World Wide Web, User modeling, Information retrieval, Social web and Semantics.
Social Semantic Web, Semantic Web, RDF, Web modeling and Web navigation are among the areas of World Wide Web where Geert-Jan Houben concentrates his study.
Geert-Jan Houben has researched Web modeling in several fields, including Web design and Web development.
He combines subjects such as Recommender system, Human–computer interaction, Adaptation and Personalization with his study of User modeling.
His Information retrieval study combines topics from a wide range of disciplines, such as Class, Extensibility and CAD.
His Semantics study integrates concerns from other disciplines, such as Social media, Microblogging, Faceted search and Service.
His most cited work include:
- AHAM: a Dexter-based reference model for adaptive hypermedia (419 citations)
- Analyzing user modeling on twitter for personalized news recommendations (314 citations)
- Adaptive hypermedia: from systems to framework (284 citations)
What are the main themes of his work throughout his whole career to date?
Geert-Jan Houben mainly focuses on World Wide Web, Semantic Web, Information retrieval, Web modeling and User modeling.
His work on Semantics expands to the thematically related World Wide Web.
His work deals with themes such as Metadata and Semantic data model, which intersect with Semantic Web.
His Web modeling research is multidisciplinary, incorporating perspectives in Web standards, Social Semantic Web, Web design and Data Web.
His Web design research is multidisciplinary, relying on both Web engineering and Web navigation.
His User modeling research includes elements of Recommender system and Human–computer interaction.
He most often published in these fields:
- World Wide Web (43.24%)
- Semantic Web (18.24%)
- Information retrieval (16.89%)
What were the highlights of his more recent work (between 2014-2021)?
- Data science (10.47%)
- World Wide Web (43.24%)
- Crowdsourcing (4.39%)
In recent papers he was focusing on the following fields of study:
His main research concerns Data science, World Wide Web, Crowdsourcing, Learning analytics and Social media.
His studies in World Wide Web integrate themes in fields like Variety and Big data.
His work carried out in the field of Crowdsourcing brings together such families of science as Identification, Annotation, Human–computer interaction, Machine learning and Bookmarking.
His research in Human–computer interaction is mostly focused on Adaptation.
His Social media research incorporates themes from User analysis, Hypertext and Urban analytics.
His Social web research focuses on Social Semantic Web and how it connects with Ontology.
Between 2014 and 2021, his most popular works were:
- Supporting Self-Regulated Learning in Online Learning Environments and MOOCs: A Systematic Review (56 citations)
- Follow the successful crowd: raising MOOC completion rates through social comparison at scale (55 citations)
- Gauging MOOC Learners' Adherence to the Designed Learning Path. (42 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- World Wide Web
Geert-Jan Houben mainly investigates Learning analytics, Mathematics education, Data science, Self-regulated learning and Multimedia.
His Learning analytics research is multidisciplinary, incorporating elements of Social psychology and Educational data mining.
His Data science study incorporates themes from Question generation, Contrast and Artificial neural network.
His studies deal with areas such as Machine learning and Artificial intelligence as well as Multimedia.
His Social web study deals with the bigger picture of World Wide Web.
The Social media research he does as part of his general World Wide Web study is frequently linked to other disciplines of science, such as Urban planning, therefore creating a link between diverse domains of science.
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