Imagine getting recommendations, for example, for music or TV shows, based on similar people you pass by on the street. No server backend needed, all via device-to-device communication. We designed and implemented such a system. You can find our full article published in IEEE Access here (PDF) and the code on GitHub. We build the … Read more
Expanding our earlier work on choice overload in related-article recommendations, we analyzed a digital library to figure out the ideal number of recommendations to show to users. Some of our metrics point toward 5-6 items as the ideal number of recommendations to display. You can find the full paper here (PDF). Choice Overload describes a … Read more
We investigate the problem of choice overload – the difficulty of making a decision when faced with many options – when displaying related-article recommendations in digital libraries. So far, research regarding to how many items should be displayed has mostly been done in the fields of media recommendations and search engines. We analyze the number … Read more
Where should an academic publish their newest work? We developed a recommender system for it. We presented this work as a paper at the HotPOST 2016 workshop (co-located with ACM MobiHoc 2016). You can find the full paper here (PDF). We analyze to what extent social relations from existing data can be utilized to generate … Read more
