Cargando…
Collaborative Filtering Recommendation on Users’ Interest Sequences
As an important factor for improving recommendations, time information has been introduced to model users’ dynamic preferences in many papers. However, the sequence of users’ behaviour is rarely studied in recommender systems. Due to the users’ unique behavior evolution patterns and personalized int...
Autores principales: | Cheng, Weijie, Yin, Guisheng, Dong, Yuxin, Dong, Hongbin, Zhang, Wansong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4873175/ https://www.ncbi.nlm.nih.gov/pubmed/27195787 http://dx.doi.org/10.1371/journal.pone.0155739 |
Ejemplares similares
-
Bidirectional Trust-Enhanced Collaborative Filtering for Point-of-Interest Recommendation
por: An, Jingmin, et al.
Publicado: (2023) -
Modeling user rating preference behavior to improve the performance of the collaborative filtering based recommender systems
por: Ayub, Mubbashir, et al.
Publicado: (2019) -
Modeling Users’ Multifaceted Interest Correlation for Social Recommendation
por: Wang, Hao, et al.
Publicado: (2020) -
POI recommendation with queuing time and user interest awareness
por: Halder, Sajal, et al.
Publicado: (2022) -
KHGCN: Knowledge-Enhanced Recommendation with Hierarchical Graph Capsule Network
por: Chen, Fukun, et al.
Publicado: (2023)