A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution
In recent years, streaming music platforms have become very popular mainly due to the huge number of songs these systems make available to users. This enormous availability means that recommendation mechanisms that help users to select the music they like need to be incorporated. However, developing...
Saved in:
| Main Authors: | Diego Sánchez-Moreno, Vivian F. López Batista, M. Dolores Muñoz Vicente, Ana B. Gil González, María N. Moreno-García |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/7309453 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Hypergraph User Embeddings and Session Contrastive Learning for POI Recommendation
by: Yan Zhang, et al.
Published: (2025-01-01) -
Let’s Play! Engaging College Students in Mini Play Sessions, Perspectives, and Reflections
by: Marna Winter
Published: (2025-03-01) -
<italic>PRIDES</italic>: A Probabilistic Model for Recurrent User Interest Drift Identification in Session-Based Recommendation
by: Vinnakota Saran Chaitanya, et al.
Published: (2025-01-01) -
Parameter-Efficiently Leveraging Session Information in Deep Learning-Based Session-Aware Sequential Recommendation
by: Jinseok Seol, et al.
Published: (2025-01-01) -
Addressing Hybrid Confounder Issue for Causal Session-Based Recommendation
by: Quan Li, et al.
Published: (2025-01-01)