DARS - Behavioral Data Analytics & Recommender Systems Lab @ University of Bergen

Department of Information Science & Media Studies
University of Bergen
Fosswinckelsgt. 6
5007 Bergen, Norway
Contact - Email: dars@uib.no


The DARS lab performs cutting-edge research in methods (e.g., AI methods to predict user behavior) and applications (e.g., intelligent user interfaces) in the context of behavioral data analytics and recommender systems. We closely collaborate with both academic and industrial partners in Norway, the EU, and beyond, contributing to Norway's national research initiative on Artificial Intelligence (AI), as well as to current AI-related research challenges in the Norwegian industry sectors. Current main research application areas of the lab include: media, finance, energy, and health. The lab is a spin-out of the Intelligent Information Systems (I2S) group at the Department of Information Science and Media Studies at the University of Bergen. The lab collaborates closely with the Centre for Data Science (CEDAS) at the University of Bergen, the Norwegian Artificial Intelligence Research Consortium (NORA), and conducts research in collaboration with a network of renowned national and international scholars in the context of behavioral data analytics and recommender systems. Outputs of the lab are published in leading conferences and journals in the field of computer & information science and interdisciplinary venues such as: NATURE Sustainability, PlosOne, JASIST, EPJ Data Science, UMUAI, WWW, ICWSM, ACM IUI, ACM UMAP, ACM SIGIR, and ACM RecSys. The core lab members have won several Best Paper/Poster Awards and Nominations, including, the Best Paper Award Honorable Mention at WWW'17. The core team is involved in the co-organization of leading conferences in their fields of research such as ACM RecSys, ACM UMAP or ACM IUI and teaches tech-related courses such as Information Systems, Advanced Programming in Python or Recommender Systems at the University of Bergen.


  • [06/2020] Christoph has been interviewed regarding our SFI application MediaFutures in the context of a #FakeNews breakfast meeting organised by NCE Media along with the CEO of Schibsted and other important media experts from NRK, TV 2, Tinius Trust, and Faktisk.no. Here the YouTube video.
  • [06/2020] Happy to announce that our paper "Visually-Aware Video Recommendation in the Cold Start" co-authored by Mehdi Elahi, Reza Hosseini, Mohammad Hossein Rimaz, Farshad Bakhshandegan Moghaddam and Christoph Trattner has been accepted at ACM Hypertext 2020 in the Blue Sky Ideas Track. Here the pre-print! PDF
  • [04/2020] Our short paper with Ayoub EL Majjodi, and Nabil EL Ioini, titled "Towards Generating Personalized Country Recommendation" has been accepted for publication at the UMAP'20 conference LBR track.
  • [04/2020] Our short paper with Anna Alexander Lambrix, Nabil EL Ioini, and Mouzhi Ge, titled "Exploring Personalized University Ranking and Recommendation" has been accepted for publication at the UMAP'20 conference LBR track.
  • [04/2020] Our short paper with Cataldo Musto and Giovanni Semeraro, titled "Towards a Knowledge-aware Food Recommender System Exploiting Holistic User Models" has been accepted for publication at the UMAP'20 conference. Christoph and Alain will present the work at July 14-17.
  • [02/2020] Happy to announce that our IKTPLUSS proposal "RE-AIMED: Readjusted responses by use of AI in medical calls" lead by NORCE has been granted by the Norwegian Science Fund! Total budget: 1.5 million EUR.
  • [01/2020] Happy to announce that the MediaFutures SFI application "Research Centre for Responsible Media Technology & Innovation" worth around 30 million EUR and which Dr. Trattner has lead as PI was submitted successfully to the Research Council of Norway :)
  • [01/2020] Our student Johnny Bjånesøy has been awarded a grant by TV2 for his work on recommender systems interfaces for online streaming services! Congrats :)
  • [01/2020] Our students Tim Soltvedt Aadland, Felipe Sepulveda and Gøran A. Slettemark have successfully defended their Master theses! Congrats :)
  • [01/2020] Work with us as a PhD student! Deadline: 29th February 2020. Here the job post!


Core Team

Assoc. Prof. Dr. Christoph Trattner [PI]
(InfoMedia @ University of Bergen)

Christoph Trattner

Christoph Trattner is an Associate Professor (permanent position) at the University of Bergen (UiB) in the Information Science & Media Studies Department. Previously to that he was an Asst. Prof. at MODUL University Vienna in the New Media Technology Department and a manager at the Know-Center, Austria's research competence for data driven business and Big Data analytics where he founded and led the Social Computing department. He holds a PhD (with distinction), an MSc (with distinction) and a BSc in Computer Science and Telematics from Graz University of Technology (Austria). Since, 2010 he co-acquired over 22 million euros in funding on European and international level in collaboration with major international industrial partners. Currently, he is leading several international research efforts that try to understand, predict and change online user behavior. He published over 100 scientific articles in top-notch venues, such as NATURE Sustainability, PlosOne, JASIST, EPJ Data Science, UMUAI, WWW, ICWSM or ACM SIGIR. He is the winner of several Best Paper/Poster Awards and Nominations, including, the Best Paper Award Honorable Mention at WWW'17.

Assoc. Prof. Dr. Mehdi Elahi [Co-PI]
(InfoMedia @ University of Bergen)

Mehdi Elahi

Mehdi Elahi is an associate professor at the University of Bergen (Norway). He received his M.Sc. degree in Electrical Engineering (Sweden) in 2010, and his Ph.D. degree in Computer Science (Italy) in 2014. Over the last 3 years, he has served as an assistant professor at the Free University of Bozen-Bolzano (Italy), where he has researched various aspects of recommender systems. He has (co-)authored more than 60 peer-reviewed publications in AI, RS, and HCI-related conferences and journals. Moreover, he has co-applied for a US-patent, and has co-authored several EU research proposals. On top of that, he has been awarded a number of industry and academic research grants, e.g., by Amazon and the Polytechnic University of Milan. He has been actively involved in the research and development of up-and-running mobile recommender systems for the food (ChefPad) and tourism domains (South Tyrol Suggests). He has provided various types of community services, such as co-organizing the ACM 2017 RecSys challenge (organized by XING), and has acted as an advisor to the 2018 RecSys challenge (organized by Spotify).

Dr. Alain Starke [Post Doc]
(InfoMedia @ University of Bergen)

Alain Starke

Alain Starke (1990) is a visiting PostDoc at the DARS lab until August 2020. He graduated cum laude at the Eindhoven University of Technology from the master's program Innovation Sciences in 2014. While writing his master's thesis, he landed a 'Research Talent' grant from the Netherlands Organization for Scientific Research (NWO) to pursue a PhD on energy recommender systems at the Human Technology Interaction group, supervised by dr.ir. Martijn Willemsen & prof.dr. Chris Snijders. Last February, he was awarded a ‘Niels Stensen Fellowship’ to fund one year of postdoctoral research on RecSys in behavioral change domains. As of September 2019, Alain has joined the DARS lab to work on psychologically-aware recommender systems in the food and news domains.

Arngeir Berge [PhD Student]
(NORCE / InfoMedia @ UiB)

Arngeir Berge

Arngeir Berge is a PhD student at the DARS lab. After obtaining his MSc at InfoMedia@UiB, he worked two years as an assist.prof. of ICT in Learning in Volda University College, before proceeding to working with e-learning, technology and multimedia in the health area. He currently works with NORCE, the Norwegian Research Centre on the project “RE-AIMED: Readjusted responses by use of AI in medical calls”, where DARS is a WP leader. In his PhD project, he studies intelligent user interfaces of recommender systems that offer decision support to medical call centre operators.

Current Master Students

  • Andira Aranadita (Centre for Nutrition @ University of Bergen)
  • Edis Asotic (InfoMedia @ University of Bergen)
  • Johnny Bjånesøy (InfoMedia @ University of Bergen)
  • Alexandra Kimberly Bobrow (InfoMedia @ University of Bergen)
  • Oyvind Johannessen (InfoMedia @ University of Bergen)
  • Tord Kvifte (InfoMedia @ University of Bergen)
  • Sebastian Øverhaug Larsen (InfoMedia @ University of Bergen)
  • Edvard Tobias Austad Lindgren (InfoMedia @ University of Bergen)
  • Jørgen Nyborg-Christensen (InfoMedia @ University of Bergen)
  • Markus Anders Pedersen (InfoMedia @ University of Bergen)
  • Arien Shibani (InfoMedia @ University of Bergen)
  • Jørgen Lie Toft (InfoMedia @ University of Bergen)
  • Markus Torgersen (Norwegian School of Economics) - MA thesis successfully defended
  • Marek Vetter (Norwegian School of Economics) - MA thesis successfully defended
  • Tim Soltvedt Aadland (InfoMedia @ University of Bergen) - MA thesis successfully defended
  • Felipe Sepulveda (InfoMedia @ University of Bergen) - MA thesis successfully defended
  • Gøran A. Slettemark (InfoMedia @ University of Bergen) - MA thesis successfully defended

Advisory Board & Collaborators

Prof. Dr. Peter Brusilovsky
(University of Pittsburgh)

Peter Brusilovsky

Peter Brusilovsky is a professor of Information science and Intelligent Systems (Artificial intelligence) at the University of Pittsburgh. He is known as one of the pioneers of Adaptive hypermedia, Adaptive Web, and Web-based Adaptive learning. He also published numerous articles in user modeling, personalization, educational technology, intelligent tutoring systems, and information access. Brusilovsky is ranked as #1 in the world in the area of Computer Education and #21 in the world in the area of World Wide Web by Microsoft Academic Search. According to Google Scholar, he has over 30,000 citations and h-index of 70. Brusilovsky's group has been awarded best paper awards at Adaptive Hypermedia, User Modeling, Hypertext, IUI, ICALT, and EC-TEL conference series. Among these awards are five prestigious James Chen Best Student paper awards.

Prof. Dr. Dietmar Jannach
(AAU Klagenfurt)

Dietmar Jannach

Dietmar Jannach is a full professor of Information Systems at AAU Klagenfurt, Austria. Before joining AAU in 2017, he was a full professor of Computer Science at TU Dortmund, Germany. In his research, he focuses on the application of intelligent system technology to practical problems and the development of methods for building knowledge-intensive software applications. In the last years, Dietmar Jannach worked on various practical aspects of recommender systems. He is the main author of the first textbook on the topic published by Cambridge University Press in 2010 and was the co-founder of a tech startup that created an award-winning product for interactive advisory solutions.

Prof. Dr. Judith Masthoff
(Utrecht University)

Judith Masthoff

Judith Masthoff is a chair in Computing Science at Utrecht University, NL. Her research is in personalisation and intelligent user interfaces. She is interested in personalizing behavior change mechanisms for encouraging people to live more healthily and sustainably, and in adapting motivating and emotional support messages to personality. She has co-organized several events such as workshops on behavior change technology, and given tutorials on personalization for behaviour change. She serves as the editor in-chief of User Modeling and User-Adapted Interaction, and has guest-edited a special issue on Personalization and Behavior Change. She is a director of User Modeling Inc., the professional association of user modeling researchers.

Prof. Dr. Francesco Ricci
(Free University of Bozen)

Francesco Ricci

Francesco Ricci is full professor and dean of the Faculty of Computer Science at the Free University of Bozen. Since November 2012 he is with the Information and Database System Engineering research area. F. Ricci has established in Bolzano a reference point for the research on Recommender Systems. He has co-edited the Recommender Systems Handbook (Springer 2011, 2015), and has been actively working in this community as President of the Steering Committee of the ACM conference on Recommender Systems (2007-2010). He was previously (from 2000 to 2006) technical director of the eCommerce and Tourism Research Lab (eCTRL) at ITC-irst (Trento, Italy). F. Ricci is author of more than one hundred fifty refereed publications and, according to Google Scholar, has H-index 52 and around 17,000 citations.

International & National Key Collaborators

Dr. Martin Atzmüller
(University of Tilburg)

Martin Atzmüller

Dr. Matthias Braunhofer

Matthias Braunhofer

Dr. Iván Cantador
(Aut. University of Madrid)

Iván Cantador

Dr. Paolo Cremonesi
(Politecnico di Milano)

Paolo Cremonesi

Dr. David Elsweiler
(University of Regensburg)

David Elsweiler

Dr. Mouzhi Ge
(Masaryk University)

Mouzhi Ge

Dr. Frode Guribye
(University of Bergen)

Frode Guribye

Dr. Eelco Herder
(Rad. Universiteit Nijmegen)

Eelco Herder

Dr. Nabil El Ioini
(Free University of Bozen)

MNabil El Ioini

Dr. Leandro Marinho

Leandro Marinho

Farshad B. Moghaddam
(Karlsruhe Institute of Tech.)

Farshad B. Moghaddam

Dr. Cataldo Musto
(University of Bari)

Cataldo Musto

Dr. Duc Tien Dang Nguyen
(University of Bergen)

Duc Tien Dang Nguyen

Dr. Andreas Opdahl
(University of Bergen)

Andreas Opdahl

Dr. Denis Parra
(PUC Chile)

Denis Parra

Dr. Neil Rubens
(Stanford University)

Neil Rubens

Dr. Alan Said
(University of Gothenburg)

Alan Said

Hanna Schäfer
(University of Konstanz)

Hanna Schäfer

Dr. Marija Slavkovik
(University of Bergen)

Marija Slavkovik

Dr. Bjørnar Tessem
(University of Bergen)

Bjørnar Tessem

Dr. Marko Tkalčič
(University of Primorska)

Marko Tkalčič

Dr. Barbara Wasson
(University of Bergen)

Barbara Wasson

Dr. Martijn Willemsen
(TU Eindhoven / Jheronimus Academy of Data Science)

Martijn Willemsen

Recent Publications

  • Visually-Aware Video Recommendation in the Cold Start . Elahi, M., Hosseini, R., Rimaz, M.H., Bakhshandegan Moghaddam, F., and Trattner, C., Proccedings of the ACM Hypertext 2020 (HT'20). Here the pre-print! PDF
  • Towards a Knowledge-aware Food Recommender System Exploiting Holistic User Models. Musto, C., Trattner, C., Starke, A.D., Semeraro, G. Proceedings of the 28th Conference on User Modeling, Adaptation and Personalization (UMAP'20), Upcoming. PDF
  • Towards Generating Personalized Country Recommendation. EL Majjodi, A., Elahi, M., EL Ioini, N., Trattner, C. Adjunct proceedings of the 28th Conference on User Modeling, Adaptation and Personalization (UMAP'20), Upcoming. PDF
  • Exploring Personalized University Ranking and Recommendation. Elahi, M., EL Ioini, N., Alexander Lambrix, A., Ge, M. Adjunct proceedings of the 28th Conference on User Modeling, Adaptation and Personalization (UMAP'20), Upcoming. PDF
  • Beyond "one-size-fits-all" platforms: Applying Campbell's paradigm to test personalized energy advice in the Netherlands. Starke, A.D., Willemsen, M.C. and Snijders, C.C.P. Energy Research and Social Science, 2020. PDF
  • With a little help from my peers: Depicting social norms in a recommender interface to promote energy conservation. Starke, A.D., Willemsen, M.C. and Snijders, C.C.P. Proceedings of the 25th International Conference of Intelligent User Interfaces (IUI), 2020. PDF
  • Learning to Recommend Similar Items from Human Judgements. Trattner, C. and Jannach, D. User Modeling and User-Adapted Interaction Journal. 2019. PDF
  • What online data say about eating habits. Trattner, C. and Elsweiler, D. NATURE Sustainability, 2019. PDF
  • Tag-Based Information Access in Image Collections: Insights from Log and Eye-Gaze Analyses. Lin, Y., Parra, D., Trattner, C. and Brusilovsky, P. Knowledge and Information Systems. 2019. PDF
  • The Roadmap to User-Controllable Social Exploratory Search. di Sciascio, C., Brusilovsky, P., Trattner, C. and Veas, E. ACM Transactions on Interactive Intelligent Systems. 2019. PDF
  • Investigating and Predicting Online Food Recipe Upload Behavior. Trattner, C., Kusmierczyk, T. and Norvag, K. Information Processing and Management. 2019. PDF
  • Movie Genome Recommender: A Novel Recommender System Based on Multimedia Content. Deldjoo, Y., Schedl, M. and Elahi, M. International Conference on Content-Based Multimedia Indexing (CBMI), 2019 PDF
  • Supporting energy-efficient choices using Rasch-based recommender interfaces. Starke, A.D. Dissertation - Eindhoven University of Technology, 2019. PDF
  • RecSys Challenges in achieving sustainable eating habits. Starke, A.D. Proceedings of the 4th workshop on Health Recommender Systems, 2019. PDF
  • The effectiveness of advice solicitation and social peers in an energy recommender system. Starke, A.D. Proceedings of the 6th Joint Workshop on Interfaces and Human Decision-making, 2019. PDF
  • Prediction of Music Pairwise Preferences from Facial Expressions. Tkalčič, M., Maleki, N., Pesek, M., Elahi, M., Ricci, F. and Marolt, M. Proceedings of the 24th International Conference on Intelligent User Interfaces (IUI), 2019. PDF
  • Exploring the Power of Visual Features for Recommendation of Movies. Rimaz, M. H., Elahi, M., Bakhshandegan Moghadam, F., Trattner, C., Hosseini, R. and Tkalčič, M. ACM Conference on User Modelling, Adaptation and Personalization (UMAP), 2019. PDF
  • Cold Start Solutions For Recommendation Systems. Moghaddam, F. B. and Elahi, M., Big Data Recommender Systems: Recent Trends and Advances, 2019. PDF
  • Analysing Recommender Systems Impact on Users’ Choices. Hazrati, N., Elahi, M. and Ricci, F. ImpactRS Workshop, 2019. PDF
  • Predicting Movie Popularity and Ratings with Visual Features. Moghaddam, F. B., Elahi, M., Hosseini, R., Trattner, C., & Tkalčič, M. IEEE SMAP, 2019. PDF
  • Content-based artwork recommendation: integrating painting metadata with neural and manually-engineered visual features. Messina, P., Dominguez, V., Parra, D., Trattner, C. and Soto, A. User Modeling and User-Adapted Interaction Journal, 2018. PDF
  • Predicting Trading Interactions in an Online Marketplace through Location-Based and Online Social Networks. Eberhard, L., Trattner, C. and Atzmueller, M. Information Retrieval Journal, 2018. PDF
  • On the Predictability of the Popularity of Online Recipes. Trattner, C., Moesslang, D. and Elsweiler, D. EPJ Data Science, 2018. PDF
  • The Impact of Recipe Features, Social Cues and Demographics on Estimating the Healthiness of Online Recipes. Rokicki, M.*, Trattner, C.* and Herder, E. (* equal contribution). In Proceedings of the 12th International AAAI conference on Web and Social Media (ICWSM), 2018. PDF
  • Food Recommender Systems: Important Contributions, Challenges and Future Research Directions. Trattner, C. and Elsweiler, D. Collaborative Recommendations: Algorithms, Practical Challenges and Applications, World Scientific Publishing Co. Pte. Ltd., 2018. PDF
  • Preference Elicitation, Rating Sparsity and Cold Start. Elahi, M., Braunhofer, M., Gurbanov, T., & Ricci, F., Collaborative Recommendations: Algorithms, Practical Challenges and Applications, World Scientific Publishing Co. Pte. Ltd., 2018. PDF

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