13 citations · 48 across the 11 of their papers we have counts for
11 papers
Narrative Information Theory
Lion Schulz, Miguel Patrício, Daan Odijk
We propose an information-theoretic framework to measure narratives, providing a formalism to understand pivotal moments, cliffhangers, and plot twists. This approach offers creati…
Does SpatioTemporal information benefit Two video summarization benchmarks?
Aashutosh Ganesh, Mirela Popa, Daan Odijk +1
An important aspect of summarizing videos is understanding the temporal context behind each part of the video to grasp what is and is not important. Video summarization models have…
Bridging the Transparency Gap: Exploring Multi-Stakeholder Preferences for Targeted Advertisement Explanations
Dina Zilbershtein, Francesco Barile, Daan Odijk +1
Limited transparency in targeted advertising on online content delivery platforms can breed mistrust for both viewers (of the content and ads) and advertisers. This user study (n=8…
Find the Cliffhanger: Multi-Modal Trailerness in Soap Operas
Carlo Bretti, Pascal Mettes, Hendrik Vincent Koops +2
Creating a trailer requires carefully picking out and piecing together brief enticing moments out of a longer video, making it a challenging and time-consuming task. This requires…
VideolandGPT: A User Study on a Conversational Recommender System
Mateo Gutierrez Granada, Dina Zilbershtein, Daan Odijk +1
This paper investigates how large language models (LLMs) can enhance recommender systems, with a specific focus on Conversational Recommender Systems that leverage user preferences…
RecFusion: A Binomial Diffusion Process for 1D Data for Recommendation
Gabriel Bénédict, Olivier Jeunen, Samuele Papa +3
In this paper we propose RecFusion, which comprise a set of diffusion models for recommendation. Unlike image data which contain spatial correlations, a user-item interaction matri…
RADio -- Rank-Aware Divergence Metrics to Measure Normative Diversity in News Recommendations
Sanne Vrijenhoek, Gabriel Bénédict, Mateo Gutierrez Granada +2
In traditional recommender system literature, diversity is often seen as the opposite of similarity, and typically defined as the distance between identified topics, categories or…
sigmoidF1: A Smooth F1 Score Surrogate Loss for Multilabel Classification
Gabriel Bénédict, Vincent Koops, Daan Odijk +1
Multiclass multilabel classification is the task of attributing multiple labels to examples via predictions. Current models formulate a reduction of the multilabel setting into eit…
Recommenders with a mission: assessing diversity in newsrecommendations
Sanne Vrijenhoek, Mesut Kaya, Nadia Metoui +3
News recommenders help users to find relevant online content and have the potential to fulfill a crucial role in a democratic society, directing the scarce attention of citizens to…
Faithfully Explaining Rankings in a News Recommender System
Maartje ter Hoeve, Anne Schuth, Daan Odijk +1
There is an increasing demand for algorithms to explain their outcomes. So far, there is no method that explains the rankings produced by a ranking algorithm. To address this gap w…
The Birth of Collective Memories: Analyzing Emerging Entities in Text Streams
David Graus, Daan Odijk, Maarten de Rijke
We study how collective memories are formed online. We do so by tracking entities that emerge in public discourse, that is, in online text streams such as social media and news str…