Dr. Christoph Trattner is currently working as an Associate Professor (permanent position) at the University of Bergen 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 an area 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 area. He holds a PhD (with distinction), an MSc (with distinction) and a BSc in Computer Science and Telematics from Graz University of Technology (Austria). He is a former FFG, Marshall Plan and ERCIM fellow and has been working at Graz University of Technology from 2009-2012 (supervised by Prof. Dr. Denis Helic & Prof. Dr. Hermann Maurer), the University of Pittsburgh from 2011-2012 (hosted by Prof. Dr. Peter Brusilovsky), the Norwegian University of Science and Technology from 2014-2015 (hosted by Prof. Dr. Kjetil Norvag), and has been visiting Yahoo! Labs Barcelona in 2014 and CWI Amsterdam in 2015 (hosted by Prof. Dr. Arjen De Vries). Christoph's research interests include Information Science, Data Science, User Modeling and Recommender Systems. He was involved, either as a collaborator or a project leader, in various national and international EU-funded research projects that dealt with social technologies and recommender systems. Currently, he is driving a research project that tries to understand, predict and change online food preferences to tackle health-related food issues such as diabetes or obesity. Since 2010, he published two books and over 80 scientific articles in top venues and journals, e.g., Wiley JASIST, ACM TiiS, Elsevier ComCom, WWW, ACM WebSci, ACM CIKM, ACM CSCW, ACM RecSys, ACM IUI, ACM HT and ACM UMAP. He is also the winner of several Best Paper/Poster Awards and Nominations, including e.g. the Best Paper Award Honorable Mention at WWW'17. He regularly acts as a PC member on several top-tier - CORE A* ranked - conferences and co-organizes or co-chaires a number of workshops and conferences.
- [07/2018] Our paper "On the Predictability of the Popularity of Online Recipes" with Moesslang, D. and Elsweiler, D. has been published in EPJ Data Science. PDF
[06/2018] Our grant proposal Investigating the impact of Artificial Intelligence on the Journalism's Social Contract - Issues of Machine Ethics in Modern Journalism with Marija Slavkovik as PI and Truls Pedersen, Helle Sjøvaag, Sjur Dyrkolbotn and me as co-applicants got accepted by the Norwegian Research council.
- [05/2018] Will be teaching a MSc course on recommender systems this fall at the University of Bergen :) Stay tuned for the teaching material!
- [04/2018] Full paper (16% quota) accepted at ICWSM'18! Title: "The Impact of Recipe Features, Social Cues and Demographics on Estimating the Healthiness of Online Recipes". PDF
- [03/2018] Was invited by the CS department at UiB to the Winter School on Algorithms. Gave an invited lecture on "Recommender Systems" and the research we do on food recommender systems. The venue was Geilo :) Awesome place to do some skiing!
- [03/2018] New book chapter on "Evaluating Group Recommender Systems" in the new Springer book on "Group Recommender Systems: An introduction" is now available. PDF
- [02/2018] There are some exciting news to share :) As of Feb. 2018 I will be joining the department of Information Science studies at the University of Bergen as
Associate Professor in Data Science (permanent position).
- [02/2018] Our work "Investigating the utility of the weather context for point of interest recommendations" was accepted for publication in the Springer journal Information Technology & Tourism. PDF
- [02/2018] Wrote a book chapter together with A. Said, L. Boratto, L. and A. Felfernig on "Evaluating Group Recommender Systems" for a new RecSys book. The book will be published soon. Title: "Group Recommender Systems: An Introduction". PDF
- [02/2018] Wrote a book chapter on "Food Recommender Systems" lately together with my friend David Elsweiler from UR. The book is a new recommender systems handbook with chapters written by many important people in the RecSys community and shall be named "Collaborative Recommendations: Algorithms, Practical Challenges and Applications".
Publication date shall be around 2018. You can download a draft from arXiv. Feedback welcome! PDF
- [10/2017] Attended RecSys'17 in Como (it was awesome) and run among other things the Health Recommender Systems Workshop. The proceedings are now online and can be downloaded
from CEUR-WS. Enjoy :)
Some recent news articles about our food research featured in the Latin American newspapers latercera.com,
Prof. Parra one of our co-authors of this work also gave an radio interview in Spanish on radio DIGITAL FM on this latest research.
Paper accepted in the Deep Learning Recommender Systems workshop held at ACM RecSys'17. Title: "Comparing Neural and Attractiveness-based Visual Features for Artwork Recommendation".
Paper accepted in the TempRS workshop held at ACM RecSys'17. Title: "TCNSVD: A Temporal and Community-Aware Recommender Approach".
On the list of the Annual Best of Computing in ACM Computing Reviews for our work on "VizRec: recommending personalized visualizations" published in ACM TiiS. Find the list here.
Paper accepted in PlosOne. Title: "Monitoring obesity prevalence in the United States through bookmarking activities in online food portals".
In July I will be off to Haifa (Israel) and to Santiago de Chile (Chile) to give two invited talks "Towards Health-aware Food Recommender Systems".
I am really looking forward to these two events organized by Prof. Tsvi Kuflik (The University of Haifa) and my friend Prof. Denis Parra (PUC, Chile).
The tentative program of the workshop in Haifa named "ISF international workshop on User Modeling and Recommender Systems", can be found here.
Paper accepted at ACM UMAP 2017. Title: "On the Relations Between Cooking Interests, Hobbies and Nutritional Values of Online Recipes: Implications for Health-Aware Recipe Recommender Systems".
Some recent news articles about our food research featured in the Austrian newspapers Kurier and derStandard and
in the German newspaper Mittelbayrische and the German radio Bayern 3.
Please consider submitting to our 23rd International Workshop on Personalized Human-Computer Interaction and Recommender Systems co-located with Mensch & Computer 2017 in Regensburg.
Please consider submitting to our International Workshop on Social Network Analysis and Digital Humanities co-located with i-Know in October 2017 in my hometown Graz.
Full Paper (22% quota) accepted at ACM SIGIR 2017. Title: "Exploiting Food Choice Biases for Healthier Recipe Recommendation".
Just received the Best Paper Award Honorable Mention at WWW'17. Reference: Investigating the Healthiness of Internet-Sourced Recipes: Implications for Meal Planning and Recommender Systems. Trattner, C. and Elsweiler, D. In Proceedings of the World Wide Web Conference (WWW), 2017.
Paper accepted at ACM Digital Health 2017. Title: "Towards Health (Aware) Recommender Systems".
Paper accepted at ACM Hypertext 2017. Title: "Tags, Titles or Q&As? Choosing Content Descriptors for Visual Recommender Systems".
Full paper (14% quota) accepted at ICWSM'17! Title: "How Editorial, Temporal and Social Biases Affect Online Food Popularity and Appreciation".
Our workshop proposal on "Health Recommender Systems" got accepted at this year's ACM RecSys conference held in Como, Italy.
Paper "Estimating the Healthiness of Internet Recipes: A cross sectional study" accepted in Frontiers in Public Health.
Latest 10 Publications
- 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. Rocicki, 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
- Evaluating Group Recommender Systems. Trattner, C., Said, A., Boratto, L. and Felfernig, A. Group Recommender Systems: An Introduction, Springer, 2018. PDF
- Investigating the utility of the weather context for point of interest recommendations. Trattner, C., Oberegger, A., Marinho, L. and Parra, D. Information Technology & Tourism, 2018. PDF
- TCNSVD: A Temporal and Community-Aware Recommender Approach.
Shahriari, M., Barth, M., Klamma, R. and Trattner, C. In Proceedings of the Temporal RecSys workshop held at ACM RecSys, 2017. PDF
- Comparing Neural and Attractiveness-based Visual Features for Artwork Recommendation.
Dominguez, V., Messina, P., Parra, D., Mery, D., Trattner, C. and Soto, A. In Proceedings of the Deep Learning RecSys workshop held at ACM RecSys, 2017. PDF
- Monitoring obesity prevalence in the United States through bookmarking activities in online food portals.
Trattner, C., Parra, D. and Elsweiler, D. PLOS ONE 12(6), 2017. PDF
- On the Relations Between Cooking Interests, Hobbies and Nutritional Values of Online Recipes: Implications for Health-Aware Recipe Recommender Systems. Trattner, C., Rocicki, M. and Herder, E.. In Proceedings of the ACM Conference on User Modeling and Personalisation (UMAP), 2017. PDF
- Exploiting Food Choice Biases for Healthier Recipe Recommendation. Elsweiler, D.*, Trattner, C.* and Harvey, M. (* equal contribution). In Proceedings of the ACM SIGIR Conference (SIGIR), 2017. PDF