What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Machine learning
Recommender system, World Wide Web, Variety, Artificial intelligence and Data science are his primary areas of study.
Many of his research projects under Recommender system are closely connected to Point with Point, tying the diverse disciplines of science together.
His World Wide Web research is multidisciplinary, relying on both User interface and Adaptation.
In his research on the topic of Variety, Transparency is strongly related with Knowledge management.
His Data science research integrates issues from Software system, Expert system and Taxonomy.
As a member of one scientific family, he mostly works in the field of Information retrieval, focusing on Service and, on occasion, Data mining.
His most cited work include:
- Recommender Systems: An Introduction (813 citations)
- Beyond accuracy: evaluating recommender systems by coverage and serendipity (393 citations)
- Recommender Systems: RECENT DEVELOPMENTS (323 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Recommender system, World Wide Web, Artificial intelligence, Information retrieval and Personalization.
The concepts of his Recommender system study are interwoven with issues in Variety, Session, Process and Data science.
Dietmar Jannach has included themes like Quality, User interface and Software engineering in his Process study.
His work on Artificial intelligence is being expanded to include thematically relevant topics such as Machine learning.
Information retrieval connects with themes related to Data mining in his study.
Dietmar Jannach combines subjects such as Task and Human–computer interaction with his study of Personalization.
He most often published in these fields:
- Recommender system (46.45%)
- World Wide Web (22.78%)
- Artificial intelligence (15.68%)
What were the highlights of his more recent work (between 2018-2021)?
- Recommender system (46.45%)
- Artificial intelligence (15.68%)
- Data science (8.28%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Recommender system, Artificial intelligence, Data science, Deep learning and Session.
His Recommender system research includes elements of Value, Preference and Personalization.
His Artificial intelligence study integrates concerns from other disciplines, such as Quality and Machine learning.
His Data science research integrates issues from Ranking, User experience design and Information system.
His Deep learning study combines topics in areas such as Field and Heuristic.
His Session research is multidisciplinary, incorporating perspectives in Class and Human–computer interaction.
Between 2018 and 2021, his most popular works were:
- Are we really making much progress? A worrying analysis of recent neural recommendation approaches (168 citations)
- Performance comparison of neural and non-neural approaches to session-based recommendation (48 citations)
- Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches (40 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Machine learning
Recommender system, Artificial intelligence, Deep learning, Data science and Session are his primary areas of study.
His Recommender system research includes themes of Ranking, Information overload and Personalization.
The study incorporates disciplines such as Class, Machine learning, User-centered design and Multimedia in addition to Artificial intelligence.
Dietmar Jannach has researched Machine learning in several fields, including Variety and Graph.
His Deep learning research incorporates themes from Radio broadcasting, Feature and Heuristic.
His studies deal with areas such as Quality, Recurrent neural network and Information retrieval, Relevance as well as Session.
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