Andreas Peintner
YOU?
Author Swipe
View article: Unsupervised Graph Embeddings for Session-based Recommendation with Item Features
Unsupervised Graph Embeddings for Session-based Recommendation with Item Features Open
In session-based recommender systems, predictions are based on the user's preceding behavior in the session. State-of-the-art sequential recommendation algorithms either use graph neural networks to model sessions in a graph or leverage th…
View article: Nuanced Music Emotion Recognition via a Semi-Supervised Multi-Relational Graph Neural Network
Nuanced Music Emotion Recognition via a Semi-Supervised Multi-Relational Graph Neural Network Open
Music emotion recognition (MER) seeks to understand the complex emotional landscapes elicited by music, acknowledging music’s profound social and psychological roles beyond traditional tasks such as genre classification or content similari…
View article: Efficient Session-based Recommendation with Contrastive Graph-based Shortest Path Search
Efficient Session-based Recommendation with Contrastive Graph-based Shortest Path Search Open
Session-based recommendation aims to predict the next item based on a set of anonymous sessions. Capturing user intent from a short interaction sequence imposes a variety of challenges since no user profiles are available and interaction d…
View article: Emotion-Based Music Recommendation from Quality Annotations and Large-Scale User-Generated Tags
Emotion-Based Music Recommendation from Quality Annotations and Large-Scale User-Generated Tags Open
Emotions constitute an important aspect when listening to music. While manual annotations from user studies grounded in psychological research on music and emotions provide a well-defined and fine-grained description of the emotions evoked…
View article: SPARE: Shortest Path Global Item Relations for Efficient Session-based Recommendation
SPARE: Shortest Path Global Item Relations for Efficient Session-based Recommendation Open
Session-based recommendation aims to predict the next item based on a set of anonymous sessions. Capturing user intent from a short interaction sequence imposes a variety of challenges since no user profiles are available and interaction d…
View article: Advances in and the Applicability of Machine Learning-Based Screening and Early Detection Approaches for Cancer: A Primer
Advances in and the Applicability of Machine Learning-Based Screening and Early Detection Approaches for Cancer: A Primer Open
Despite the efforts of the past decades, cancer is still among the key drivers of global mortality. To increase the detection rates, screening programs and other efforts to improve early detection were initiated to cover the populations at…
View article: Automated spheroid generation, drug application and efficacy screening using a deep learning classification: a feasibility study
Automated spheroid generation, drug application and efficacy screening using a deep learning classification: a feasibility study Open
The last two decades saw the establishment of three-dimensional (3D) cell cultures as an acknowledged tool to investigate cell behaviour in a tissue-like environment. Cells growing in spheroids differentiate and develop different character…