133 citations · 249 across the 13 of their papers we have counts for
13 papers
A Survey on Popularity Bias in Recommender Systems
Anastasiia Klimashevskaia, Dietmar Jannach, Mehdi Elahi +1
Recommender systems help people find relevant content in a personalized way. One main promise of such systems is that they are able to increase the visibility of items in the long…
Changing Salty Food Preferences with Visual and Textual Explanations in a Search Interface
Arngeir Berge, Vegard Velle Sjøen, Alain D. Starke +1
Salt is consumed at too high levels in the general population, causing high blood pressure and related health problems. In this paper, we present results of ongoing research that t…
ACM RecSys 2018 Late-Breaking Results Proceedings
Christoph Trattner, Vanessa Murdock, Steven Chang
The ACM RecSys'18 Late-Breaking Results track (previously known as the Poster track) is part of the main program of the 2018 ACM Conference on Recommender Systems in Vancouver, Can…
Food Recommender Systems: Important Contributions, Challenges and Future Research Directions
Christoph Trattner, David Elsweiler
The recommendation of food items is important for many reasons. Attaining cooking inspiration via digital sources is becoming evermore popular; as are systems, which recommend othe…
Comparing Neural and Attractiveness-based Visual Features for Artwork Recommendation
Vicente Dominguez, Pablo Messina, Denis Parra +3
Advances in image processing and computer vision in the latest years have brought about the use of visual features in artwork recommendation. Recent works have shown that visual fe…
Exploring Content-based Artwork Recommendation with Metadata and Visual Features
Pablo Messina, Vicente Dominguez, Denis Parra +2
Compared to other areas, artwork recommendation has received little attention, despite the continuous growth of the artwork market. Previous research has relied on ratings and meta…