Music recommendation systems: Techniques, use cases, and challenges
This chapter gives an introduction to music recommender systems, considering the unique
characteristics of the music domain. We take a user-centric perspective, by organizing our …
characteristics of the music domain. We take a user-centric perspective, by organizing our …
Making neural networks interpretable with attribution: application to implicit signals prediction
D Afchar, R Hennequin - Proceedings of the 14th ACM conference on …, 2020 - dl.acm.org
Explaining recommendations enables users to understand whether recommended items are
relevant to their needs and has been shown to increase their trust in the system. More …
relevant to their needs and has been shown to increase their trust in the system. More …
On skipping behaviour types in music streaming sessions
The ability to skip songs is a core feature in modern online streaming services. Its
introduction has led to a new music listening paradigm and has changed the way users …
introduction has led to a new music listening paradigm and has changed the way users …
Why people skip music? On predicting music skips using deep reinforcement learning
Music recommender systems are an integral part of our daily life. Recent research has seen
a significant effort around black-box recommender based approaches such as Deep …
a significant effort around black-box recommender based approaches such as Deep …
Deep attentive study session dropout prediction in mobile learning environment
Student dropout prediction provides an opportunity to improve student engagement, which
maximizes the overall effectiveness of learning experiences. However, researches on …
maximizes the overall effectiveness of learning experiences. However, researches on …
Effective music skip prediction based on late fusion architecture for user-interaction noise
S Jin, J Lee - Expert Systems with Applications, 2024 - Elsevier
Music skip prediction aims to predict whether user skips occur in upcoming songs during a
playlist streaming session. The track features representing musical characteristics, such as …
playlist streaming session. The track features representing musical characteristics, such as …
[PDF][PDF] Tracing Knowledge for Tracing Dropouts: Multi-Task Training for Study Session Dropout Prediction.
Study session dropout prediction allows for educational systems to identify when a student
would stop a study session which gives vital information to prolong learning activity. Student …
would stop a study session which gives vital information to prolong learning activity. Student …
Interpretable Music Recommender Systems
D Afchar - 2023 - theses.hal.science
''Why do they keep recommending me this music track?''''Why did our system recommend
these tracks to users?''Nowadays, streaming platforms are the most common way to listen to …
these tracks to users?''Nowadays, streaming platforms are the most common way to listen to …
Contextual compositionality detection with external knowledge bases and word embeddings
When the meaning of a phrase cannot be inferred from the individual meanings of its words
(eg, hot dog), that phrase is said to be non-compositional. Automatic compositionality …
(eg, hot dog), that phrase is said to be non-compositional. Automatic compositionality …
The users' behaviour in audio streaming services: investigations in the music and podcast domains
F Meggetto - 2024 - stax.strath.ac.uk
In recent years, online audio streaming services (eg, Amazon Music and Spotify) have
witnessed an increase in popularity due to content digitisation. These platforms, now offering …
witnessed an increase in popularity due to content digitisation. These platforms, now offering …