Cargando…
(CF)(2) architecture: contextual collaborative filtering
Recommender systems have dramatically changed the way we consume content. Internet applications rely on these systems to help users navigate among the ever-increasing number of choices available. However, most current systems ignore the fact that user preferences can change according to context, res...
Autores principales: | Bachmann, Dennis, Grolinger, Katarina, ElYamany, Hany, Higashino, Wilson, Capretz, Miriam, Fekri, Majid, Gopalakrishnan, Bala |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6413629/ https://www.ncbi.nlm.nih.gov/pubmed/30956536 http://dx.doi.org/10.1007/s10791-018-9332-3 |
Ejemplares similares
-
Data Augmentation for Deep-Learning-Based Multiclass Structural Damage Detection Using Limited Information
por: Dunphy, Kyle, et al.
Publicado: (2022) -
A study of an adaptive replication framework for orchestrated composite web services
por: Mohamed, Marwa F, et al.
Publicado: (2013) -
Alignment-free filtering for cfNA fusion fragments
por: Yang, Xiao, et al.
Publicado: (2019) -
Collaborative Filtering Recommendation of Music MOOC Resources Based on Spark Architecture
por: Wang, Lifu
Publicado: (2022) -
Contextualized Filtering for Shared Cyber Threat Information
por: Dimitriadis, Athanasios, et al.
Publicado: (2021)