H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 51 Citations 11,208 229 World Ranking 2767 National Ranking 17

Overview

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.

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.

Top Publications

Recommender Systems: An Introduction

Dietmar Jannach;Markus Zanker;Alexander Felfernig;Gerhard Friedrich.
(2010)

1812 Citations

Beyond accuracy: evaluating recommender systems by coverage and serendipity

Mouzhi Ge;Carla Delgado-Battenfeld;Dietmar Jannach.
conference on recommender systems (2010)

600 Citations

Recommender Systems: RECENT DEVELOPMENTS

Dietmar Jannach;Markus Zanker;Alexander Felfernig;Gerhard Friedrich.
(2010)

506 Citations

Conceptual modeling for configuration of mass-customizable products

Alexander Felfernig;Gerhard Friedrich;Dietmar Jannach.
Artificial Intelligence in Engineering (2001)

254 Citations

Consistency-based diagnosis of configuration knowledge bases

Alexander Felfernig;Gerhard Friedrich;Dietmar Jannach;Markus Stumptner.
Artificial Intelligence (2004)

248 Citations

UML AS DOMAIN SPECIFIC LANGUAGE FOR THE CONSTRUCTION OF KNOWLEDGE-BASED CONFIGURATION SYSTEMS

Alexander Felfernig;Gerhard E. Friedrich;Dietmar Jannach.
International Journal of Software Engineering and Knowledge Engineering (2000)

234 Citations

An Integrated Environment for the Development of Knowledge-Based Recommender Applications

Alexander Felfernig;Gerhard Friedrich;Dietmar Jannach;Markus Zanker.
International Journal of Electronic Commerce (2006)

214 Citations

When Recurrent Neural Networks meet the Neighborhood for Session-Based Recommendation

Dietmar Jannach;Malte Ludewig.
conference on recommender systems (2017)

213 Citations

How should I explain? A comparison of different explanation types for recommender systems

Fatih Gedikli;Dietmar Jannach;Mouzhi Ge.
International Journal of Human-computer Studies / International Journal of Man-machine Studies (2014)

203 Citations

Automated Generation of Music Playlists: Survey and Experiments

Geoffray Bonnin;Dietmar Jannach.
ACM Computing Surveys (2014)

200 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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