Research is facing a reproducibility crisis, in which the results and
fi...
Recent research has suggested different metrics to measure the inconsist...
For a long time, machine learning (ML) has been seen as the abstract pro...
In this work, we tackle the problem of adapting a real-time recommender
...
Data and algorithm sharing is an imperative part of data and AI-driven
e...
The use of data-driven decision support by public agencies is becoming m...
User-based KNN recommender systems (UserKNN) utilize the rating data of ...
In this industry talk at ECIR'2022, we illustrate how to build a modern
...
Multimedia recommender systems suggest media items, e.g., songs, (digita...
Personalized news recommender systems support readers in finding the rig...
In this position paper, we discuss the merits of simulating privacy dyna...
Several studies have identified discrepancies between the popularity of ...
Music recommender systems have become an integral part of music streamin...
In this paper, we explore the reproducibility of MetaMF, a meta matrix
f...
Music preferences are strongly shaped by the cultural and socio-economic...
In this work, we study the utility of graph embeddings to generate laten...
In this paper, we introduce a psychology-inspired approach to model and
...
In this paper, we present our work to support publishers and editors in
...
This work addresses the problem of providing and evaluating recommendati...
In our work [KPL17], we study temporal usage patterns of Twitter hashtag...
Music recommender systems have become central parts of popular streaming...
User-based Collaborative Filtering (CF) is one of the most popular appro...
Recommender systems have become important tools to support users in
iden...
In this work, we propose a content-based recommendation approach to incr...
The micro-blogging platform Twitter allows its nearly 320 million monthl...
In this paper, we present work-in-progress on applying user pre-filterin...
In this paper, we present preliminary results of AFEL-REC, a recommender...
User-based Collaborative Filtering (CF) is one of the most popular appro...
With the emergence of Web 2.0, tag recommenders have become important to...
In this paper, we study the imbalance between current state-of-the-art t...
This thesis was submitted by Dr. Dominik Kowald to the Institute of
Inte...
In this paper, we present the results of an online study with the aim to...
In this work, we address the problem of recommending jobs to university
...