TY  - JOUR
TI  - AN ENSEMBLE MODEL FOR COLLABORATIVE FILTERING TO INVOLVE ALL ASPECTS OF DATASET
AB  - The accuracy of predictions is better if the combinations of thedifferent approaches are used. Currently in collaborative filtering research, thelinear blending of various methods is used. More accurate classifiers can beobtained by combining less accurate ones. This approach is called ensembles ofclassifiers. Different collaborative filtering methods uncover the different aspectsof the dataset. Some of them are good at finding out local relationships; the otherswork for the global characterization of the data. Ensembles of differentcollaborative filtering algorithms can be created to provide more accuraterecommender systems.
AU  - AR, Yılmaz
DO  - 10.1501/commua1-2_0000000112
PY  - 2018
JO  - Communications Faculty of Sciences University of Ankara Series A2-A3: Physical Sciences and Engineering
VL  - 60
IS  - 2
SN  - 1303-6009
SP  - 15
EP  - 26
DB  - TRDizin
UR  - http://search/yayin/detay/376905
ER  -