- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
1433-3058
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Anmerkungen
-
online resource.
- Erschienen in
-
Evolving temporal association rules in recommender system ; day:22 ; month:10 ; year:2017 ; pages:1-15
Neural computing & applications ; (22.10.2017), 1-15
- Urheber
-
Zhou, Huiyu
- Beteiligte Personen und Organisationen
-
Hirasawa, Kotaro
SpringerLink (Online service)
- DOI
-
10.1007/s00521-017-3217-z
- URN
-
urn:nbn:de:1111-201712171284
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:20 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Zhou, Huiyu
- Hirasawa, Kotaro
- SpringerLink (Online service)
Ähnliche Objekte (12)
Identification of co-evolving temporal networks
Introduction of temporal and spatial dimensions into a recommender system
Recommender Systems
TSCMF: Temporal and social collective matrix factorization model for recommender systems
Identification of temporal association rules from time-series microarray data sets
Rules of Origin: Evolving Best Practices for RTAs/FTAs
Benchmarking recommender systems
Contextual Personality-Aware Recommender System Versus Big Data Recommender System
Contextual Personality-Aware Recommender System Versus Big Data Recommender System
Recommender systems based on neuro-symbolic knowledge graph embeddings encoding first-order logic rules
Discovering Evolving Temporal Information: Theory and Application to Clinical Databases
SPATIO-TEMPORAL DATA MODEL FOR INTEGRATING EVOLVING NATION-LEVEL DATASETS
Identification of co-evolving temporal networks
Introduction of temporal and spatial dimensions into a recommender system
Recommender Systems
TSCMF: Temporal and social collective matrix factorization model for recommender systems
Identification of temporal association rules from time-series microarray data sets
Rules of Origin: Evolving Best Practices for RTAs/FTAs
Benchmarking recommender systems
Contextual Personality-Aware Recommender System Versus Big Data Recommender System
Contextual Personality-Aware Recommender System Versus Big Data Recommender System
Recommender systems based on neuro-symbolic knowledge graph embeddings encoding first-order logic rules
Discovering Evolving Temporal Information: Theory and Application to Clinical Databases
SPATIO-TEMPORAL DATA MODEL FOR INTEGRATING EVOLVING NATION-LEVEL DATASETS
Identification of co-evolving temporal networks
Introduction of temporal and spatial dimensions into a recommender system
Recommender Systems
TSCMF: Temporal and social collective matrix factorization model for recommender systems
Identification of temporal association rules from time-series microarray data sets
Rules of Origin: Evolving Best Practices for RTAs/FTAs
Benchmarking recommender systems
Contextual Personality-Aware Recommender System Versus Big Data Recommender System
Contextual Personality-Aware Recommender System Versus Big Data Recommender System
Recommender systems based on neuro-symbolic knowledge graph embeddings encoding first-order logic rules
Discovering Evolving Temporal Information: Theory and Application to Clinical Databases